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Yadong Jiang,1 Qunbo Lv,2 Dong Liu,3 Dengwei Zhang,3 Bin Xue4
1Univ. of Electronic Science and Technology of China (China) 2Aerospace Information Research Institute, Chinese Academy of Sciences (China) 3Zhejiang Univ. (China) 4Tianjin Univ. (China)
This PDF file contains the front matter associated with SPIE Proceedings Volume 12065, including the Title Page, Copyright information, and Table of Contents
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Clouds play an important role in weather and climate-related investigations. However, they often influence the quality of images and waste resources of storage and bandwidth in remote sensing. So, it is critical to detect clouds for less cost of payload. In this paper, the design of a real-time cloud detection camera for small satellite platforms is proposed based on field programmable gate array (FPGA). Two MicroBlaze Soft Cores are embedded in the FPGA to accomplish the task without other chips assist. By using this way, the system is highly programmable and integrated, the weight of which also becomes lighter. We implemented the system on a Xilinx Virtex-4 FPGA. The test results show that the signal-to-noise ratio (SNR) is 128.1 at 80% of the saturated exposure. We select Arabian Peninsula-Pakistan-West India area to evaluate the cloud judgment accuracy. Compare with moderate resolution imaging spectroradiometer (MODIS) cloud mask products, the false alarm rate (FAR) is less than 3%. The application of the proposed approach in a simulation and engineering system indicates its effectiveness and practicability.
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Helicopters are widely used due to their excellent low-altitude flight characteristics and convenient take-off and landing advantages. However, the densely distributed wires in the low-altitude environment have always been a huge threat to helicopters, and they are known as aerial "trips". Because of its ability to detect small obstacles in three dimensions, lidar has gradually become an important sensor to solve the problem of helicopter low-altitude line collision. This article first introduces the current lidar point cloud wire detection method, and then proposes a new point cloud wire detection method that can be used for helicopter obstacle avoidance. This method uses rough extraction, clustering, identification and fitting display steps. The symbolic prompts for wires and dangerous obstacles are realized. Experiments show that this method has high real-time characteristics on the basis of ensuring effective detection, and is suitable for wire detection in helicopter obstacle avoidance scenarios.
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The ultimate detection limits based on gas absorption detection techniques are always of interest to researchers. Regardless of the detection limits established by various systems, gas absorption itself has an unbreakable constraint, namely the inherent limit (IL), which refers to the theoretical limit when only one gas molecule can participate in the absorption in the lower-state level. When the number of molecules in the lower-state is extended to n, the number of molecules of the absorbed species on effective optical path is considered as n·IL. This phenomenon is interpreted as the absorption quantization, and IL is considered as the smallest unit of quantization. The IL obtained by establishing a certain theoretical analysis can be determined under a definite detection conditions, such as absorbed species, specific absorption transition, temperature. The R(76) line near 2390.522470 cm-1 of CO2 and P(7) line near 2115.628975 cm-1 of CO are chosen to explore IL at different temperatures and corresponding absorption. Furthermore, a constructive method has been proposed to change the IL.
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For two linear / three linear array mapping cameras, the on-orbit angle change between mapping cameras / star earth cameras is the key to affect the accuracy of mapping / no control point positioning. In this paper, the on-orbit optical axis pointing change of a high-precision stereo mapping camera is evaluated, which is based on the on-orbit monitor system of boresight angle change between front and rear view camera/star cameras. Firstly, the spot image quality evaluation of the boresight position recorder of star earth cameras is carried out. It mainly includes shape, gray value, noise and so on. Secondly, the optical axis pointing stability of star earth cameras is analyzed. Finally, the optical axis pointing accuracy is analyzed. The results show that the performance of boresight position recorder of star earth cameras is good after on-orbit parameter optimization, the boresight pointing accuracy of star earth cameras is better than 0.2″, focus accuracy is better than 0.005mm. It provides a good reference for the follow-up project promotion.
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Researchers have proposed beam-splitting imaging methods to solve the problem that capturing the simultaneous view by multiple imaging instruments and positionally aligning them pixel by pixel. Beam-splitting prism and beam-splitting plate are two kinds of commonly used beam-splitting devices. However, which kind of the two devices degrade images to a less extent lacks discussion. Firstly, we theoretically analyzed possible image degradation caused by beam-splitting devices, which mainly include spherical aberration, ghost effect, a non-uniformity of the degradation function, and color cast. And we used ZEMAX optical simulation software to establish a beam-splitting imaging emulation experiment to simulate the image degradations mentioned above. we constructed an experience system of beam-splitting imaging in the laboratory. researchers could select a suitable device for their projects based on our study.
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In the camera calibration process, the checkerboard pattern has a wide range of applications. Aiming at the current checkerboard corner detection algorithms that have missed and misdetected situations, this paper proposes an automatic checkerboard corner detection algorithm that combines gray-scale features and energy minimization(ADGE). The ADGE first uses the proposed two sets of gray-level symmetry operators to process the image separately to extract the candidate corner points, and then uses the regional block mode to dynamically search for the local maximum value of the candidate corner points. It further constructs a reaction function to linearly solve the sub-pixel coordinates, and finally extracts all checkerboard corner points and sorts them by minimizing the energy function. Experimental results show that the corner points extracted by the ADGE have no missed and false detection, and the corner reprojection accuracy is 0.1298 pixels. The ADGE can meet the requirements of camera calibration and provide it with high-precision data.
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An all-angle directions (AAD) evaluation method of laser spot is presented in the paper. The mathematical model for calculating the spot size at any angle is established firstly. Then, laser spot width of multiple typical angles is measured by the AAD evaluation method. Compared with the result of the traditional measurement in the horizontal and vertical directions through mechanical rotation, the differences are less than 0.15%. The differences in pixel points between the profile of the spot drawn by the laser spot obtained at different rotation angles on the detection surface are all less than 2.28%. The method can fully reflect the asymmetrical distribution of the laser spot without moving the equipment or the laser source, and avoid the influence of mechanical errors.
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Transport of intensity equation (TIE) is an established quantitative phase imaging (QPI) method as a deter-ministic phase retrieval algorithm derived from paraxial approximation. However, this approximation limits TIE to retrieve high-resolution QPI for most biological samples. It can be overcome via the phase transfer function (PTF) method (no paraxial approximation), while it has incorrect phase in low-frequency due to the weak phase approximation. For the general microscopic specimens with thickness and small details, we present a resolution-enhanced QPI mixed-transfer-function (MTF) approach based on the spatial domain and the spatial frequency one, using phase space theory as a bridge. It is proved that the traditional TIE can obtain the accurate phase in low-frequency, but suffers from attenuation and blurring at high frequencies. Thus, MTF is combined with PTF to improve the maximum resolution that can be accurately reconstructed. Simulation results and experiments demonstrate that MTF can achieve high-contrast and high-resolution QPI correctly over the whole theoretical bandwidth, showing efficiency for phase retrieval even in slowly varying large phase objects. Besides, it is compatible with commercial microscopes without additional hardware modification, offering a flexible and cost-effective alternative for biomedical research and cellular investigations.
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With the advantages of large detection and abundant information, time-domain electromagnetic survey has become the most potential and significant method technology in the field of electromagnetic survey. However, this technology is still under development in China, there is no system with practical detection been formed at present. This paper has proposed a method of building the airborne time-domain electromagnetic system based on fixed-wing UAV, which aims to realize the information and intelligent detection in the complex area through "manned platform with manned system". The system is designed as follows. The transmitter wires which are designed into three circle are fixed on the UAV nose, wing tip and belly fin, which can transmit once electromagnetic field to detect and whose maximum emission moment can reach 62100A·㎡. The receiving system which is fixed under the UAV belly can receive the secondary electromagnetic field from ground. The collection monitoring system which is fixed in the UAV belly is used to data recording and states monitoring including the power of transmitter wires, the positon of receiving system and the tension of towing current conversion and data recording. The circle and length of the transmitter wires could be intelligently adjusted with the UAV and application tasks and the releasing program will be intelligently started in emergency. Above all, the research proposed in this paper can provide a good conference for the application and practical of time-domain electromagnetic survey.
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Based on the current development situation, this paper introduces the development strategies, policies, key equipment and research situation of unmanned ground vehicles (UGV) around the world. The present situation of UGVs is summarized into two main points. Firstly, the development progress of military unmanned ground autonomous systems is accelerated. And, secondly, the logistics UGV and armed autonomous UGV have been highlighted. In this paper, the development tendencies and the technical challenges of UGV are analyzed. The technologies to be developed in the future mainly include command and control (C2), communication, artificial intelligence (AI), and all-electric or hybrid electric drive (HED). Accelerating the research on intelligent UGVs is the key to win the information war in the future.
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The current evaluation standard of fiber optic current sensor (FOCS) is messy and single, which cannot consider the accuracy and stability simultaneously. The analytic hierarchy process (AHP) method has been proposed to evaluate the comprehensive performance of FOCS. The complete evaluation system is designed, which lays a solid foundation for the scientific evaluation of FOCS,especially for microcurrent measurement.
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In order to improve the target localization accuracy for unmanned aerial vehicle(UAV), a novel resolved case for target accurately localization is proposed using slave-INS which is fixed on electro-optical reconnaissance system. The work flow of this case is presented, the coordinate transformation relation in target localization process is deduced. According to requirement, a slave-INS alignment on moving base using master INS data is designed. Carry out experiment upon vehicular navigation system, the error convergence of azimuth accelerated obviously. The accuracy of azimuth reaches about 0.1°(1 σ). Experiment results show that the localization accuracy for ground target can reach 6m when UAV flies at about 3500m above ground and slant distance is 3700m. the INS has convenience and flexible use which meet to requirement of target localization in electro-optical reconnaissance system on UAV. The accuracy of localization can be increased prominently when this INS is applied to target localization technology. With great practical value.
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Space target detection and recognition is the premise of competing for the advantage of space information and the important data source of space situation awareness. With the increasing space activities and threats such as space rendezvous and emergency launch, the demand for emergency detection and identification of space targets is becoming more and more urgent, and the demand for fast emergency and high-precision measurement of optical characteristics of space targets is also put forward. This paper introduces the space target observation information processing system based on camera array, which is being developed. The system is mainly used for space non cooperative target emergency measurement, and mainly includes four parts: firstly, the hardware basis of the whole information system is camera array optical measurement system; secondly, the system is based on STK and MATLAB two software joint platform, through the interface provided by STK/Connect and MATLAB interactive connection, through the MATLAB commands and instruction set to achieve the interactive use of data between the two software, as well as the collection and creation of charts and reports; third, the key technology of software development, namely the main function module The module mainly includes: initial orbit determination, orbit prediction, space target feature extraction based on optical characteristics, and space target recognition; finally, the whole software system is developed through the integration of the above four functional modules
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In recent years, the optical fiber sensing technology has attracted social more and more attention because it has advantages of strong anti-interference ability, corrosion resistance and high sensitivity. So the research of the optical fiber sensing technology has become a hot issue for researchers. Fiber Bragg grating(FBG) sensing is a kind of optical fiber sensing, and the transmission spectrum or reflection spectrum is affected by the change of external environment. The research of this topic is tilted fiber Bragg gratings(TFBG), there are core modes and a large number of cladding modes in the transmission spectrum of TFBG sensor, which will change with the change of the external environment, so it is of great significance to study its transmission spectrum with the external changes.Firstly, the temperature and refractive index sensing performance of TFBG by Optigrating. Then we measures the temperature sensing, refractive index sensing and strain sensing of the TFBG sensor, and the tilt angle is 8°, the period is 530nm, the modulation depth is grater than15dB, and the experimental results are consistent with the simulation results. We obtained that the temperature sensitivity of the TFBG is 10pm/℃ in the measurement range of 20℃-150℃, and the refractive index sensitivity is 3.2pm/% in the range of 0-25%NaCl solution, and the stress sensitivity is 1.593nm/mm in the range of 0-1.2mm tensile length in our experiment. Therefore, the TFBG sensor has important applications in many fields.
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In this paper, three algorithms are proposed to restore the fog-containing relative intensity image of lidar based on the atmospheric scattering model and dark channel prior theory. The algorithm was evaluated by analyzing the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of the two data sets, including the fog-free relative intensity images and the fog-containing relative intensity images and standard fog-free relative intensity images. The experimental results show that the PSNR of the two groups of data can be improved by the three algorithms to varying degrees, and the highest PSNR can reach 35.6%. The structure similarity SSIM was significantly improved, and the effect was up to three orders of magnitude.
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The magnetic-thermal coupling effect, which can result in a serious non-reciprocal error, can’t be ignored in high-performance depolarized interferometric fiber optic gyroscope (De-IFOG). In this paper, we research on the magnetic-thermal coupling effect under varying temperature field in De-IFOG theoretically and experimentally. The mechanism of the coupling effect is thoroughly investigated and the related theoretical calculation model is established. The essential differences between the errors caused by varying temperature field and magnetic-varying temperature field are analyzed respectively. Simulations and experiments are consistent with the theoretical model. The experimental results show that, when the temperature varies from -30℃ to 20℃ at the speed of 14℃/h, the peak to peak value of error is up to 35 °/h with a constant magnetic field of 10 Gauss. The results can be used to enhance environmental adaptability of devices such as De-IFOGs, which are in great demands for aerospace applications.
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High-index contrast subwavelength gratings(HCG)for 940 nm GaAs-based VCSELs were presented. The structural characteristics of TM-HCG is analyzed, especially the influence of the grating parameters on the high reflection band. The 940nm TM-HCG has a large reflection bandwidth up to 188nm (Δ λ / λ 0 = 20%) with its reflectivity more than 99.5% for TM incident light, and reflectivity is less than 67.5% for TE incident light. So the HCG exhibits large high reflectivity bandwidth and polarization selectivity.
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This paper aims at the application requirements of target localization in specific environments, a method based on single scattering of polarized ultraviolet light to achieve non-line-of-sight target localization is proposed. In this paper, the target positioning is completed by combining with the obtained target azimuth angle and distance. Firstly, in this paper, based on the non-coplanar single scattering channel model of a spherical coordinate system, combining with the transmission characteristic of atmospheric scattering of polarized ultraviolet light, the single scattering model of polarized ultraviolet light is established for the non-line-of-sight targets which are not at the same height. The polarization scattering transmission characteristics of ultraviolet light and the variation of the radiation intensity were analyzed by the method of matrix optics. Thus a relationship between the received light intensity and the azimuth angle and the distance between transmitter and receiver was established. Then, matlab software is used to simulate and analyze the effect of the distance between transmitter and receiver on the received light intensity under the condition of the maximum receiving light intensity during sunny and smog days. Finally, the effect of the elevation error of the receiver and the transmitter on target positioning is simulated and analyzed. At the distance between transmitter and receiver of 400m, the distance measurement error is 20.6m on sunny days and 26m on smog days when the transmitter and receiver elevation angle deviates 3° (the preset transmit elevation angle is 35° and receive elevation angle is 25°). In addition, the background light affects determination of the azimuth angle but has a small impact on the ranging. In order to achieve accurate target positioning, this paper proposes effective improvement measures for the above possible errors.
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In view of the detection requirements of "low slow and small" targets in the air, this paper introduces a kind of folded and reverse type near infrared television camera. The initial structure design of large aperture near infrared optical system is completed by using the characteristics of refraction optical system and reflective optical system. The focal length is 1200mm and f # is 10. The system is optimized by code V software. Optical transfer function and dispersion circle are used as the evaluation criteria. The image quality of the system reaches the diffraction limit. In this paper, the optical system selection, optical material selection, aberration analysis and other aspects are considered, and the folded optical scheme is proposed. The system blocking ratio is less than 28%, and the distortion is less than 0.5%. The transfer function is close to the diffraction limit, and MTF is more than 0.25 at 50lp/mm. The diameter of dispersion element is the same as the pixel size of detector, and the energy utilization rate is high. Then, the system structure design is completed, and the stray light analysis is completed for the optical machine model and the suppression measures are put forward to ensure the clear observation image of the whole market.
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In this paper, a homogeneous off-axis reflective infrared imaging system with an aperture of Φ300mm is designed according to the requirements. The calculation and optimization of structural parameters are completed in the optical software Code V. The system obscuration is eliminated by combining aperture off-axis with off-axis field of view. By introducing complex surface type to correct the residual aberrations, the off-axis optical system with good capability and structure size meeting the overall layout requirements is obtained. The system is composed by main reflector (F-1), secondary mirror (F-2), plane mirror (M) and the third mirror (F-3). The mirror M is a folding reflector; even aspheric surface is used for both F-1, F-2 and F-3 mirror. The uncooled thermal imager is used as the imaging device. The target plane of the detector is 10.88mm × 8.70mm, and the corresponding field of view is 0.6 °× 0.45 °. At 15lp / mm, MTF > 0.2 is close to the diffraction limit of the system, and the wavefront aberration of the full field of view is less than 0.01λ. The distortion is less than 1.2%.
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In this paper, in order to track and measure the long-distance target, a continuous zoom optical system with a diameter of 400mm and focal length of 1000mm-4000mm is designed. The imaging quality evaluation of optical system is mainly carried out from the following five aspects: field curvature, distortion, transfer function MTF of optical system, energy concentration and spot array. Through the simulation calculation of image quality, the performance of optical system meets the requirements of clear imaging.
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This paper uses the non certificate identification public key ipk technology based on SM2 algorithm to establish a point-to-point lightweight security system between the ground station and the UAV, and provides a kind of security reinforcement and identification technology of flight control instructions for the safe and stable operation of the UAV, which realizes the effective identification of remote flight control instructions by the UAV, and effectively prevents the illegal intrusion and malicious software damage of the UAV, This technology realizes the autonomous decision-making of UAV for command execution and the active defense of UAV system, and ensures the flight safety and autonomous control of UAV.
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Underwater optical imaging has important application value, but it is also challenging. In traditional underwater imaging, the problems of uneven illumination, blurred texture details and low contrast often exist, in this paper we propose an underwater active polarization imaging algorithm based on low-rank sparse decomposition aiming to solve the problems above. According to the principle of underwater polarization imaging, the algorithm first performs target information enhancement on the acquired polarization images. Then combining with the low-rank characteristics of backscatter images in the scattered light field, the background information and target information could be separated from the captured images by the low-rank sparse decomposition principle, the high-quality image could be recovered from turbid water as a result. The results of experimental treatments with different turbidity levels demonstrate that the underwater polarization imaging algorithm based on low-rank sparse decomposition can improve the contrast of images, maintain the details of images and remove the background scattering at the same time. Moreover, the proposed method can effectively recover multiple targets and significantly improve the imaging quality which provides a new idea for underwater polarization clear imaging detection.
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Aiming at the problem that the background noise mixed in the target echo will affect the calculation of the target polarization degree when the traditional polarization detection system obtains the target polarization degree, based on the polarization Gm-APD detection model, a set of target echo polarization correction method is proposed. The target is imaged in a xenon lamp environment, the influence of target attitude and polarization angle on detection is explored, and the polarization imaging results are analyzed. The results show that the polarization system has a significant effect on metal materials with low surface roughness. When circularly polarized light is incident, the echo trigger probability of the metal material reaches a peak at the polarization angle of 135°. The greater the incident angle, the greater the echo depolarization and the lower the trigger probability. By inverting the distribution of echo photons, the number of background noise photons in the echo and the number of target echo photons can be obtained respectively, and a more accurate correction of the polarization degree of the target echo can be obtained. For metal materials, when the target attitude angle is 30°, the target polarization before and after correction are 0.47 and 0.57 respectively, and the target echo polarization after correction is 7% higher than that without correction. This research work provides experimental support for the effective detection and target detection of GM-APD lidar in the daytime.
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Bi-directional reflection distribution function (BRDF) is a common method to study the laser scattering characteristics of targets, and it is an important parameter for the theoretical demonstration of laser active detection, target recognition and classification. Scholars at home and abroad have proposed many mature BRDF models to describe the scattering characteristics of different targets. However, almost all of these models do not take into account the effect of incident wavelength on scattering characteristics. In addition, limited by the frequency modulation range of the laser, the existing BRDF measurement devices cannot obtain the BRDF data of the target at any wavelength, which restricts the application of the existing BRDF model. In view of this limitation, a method is proposed to calculate the unknown wavelength BRDF data using the BRDF measurement data of known wavelengths. Firstly, based on the Kirchhoff approximation theory, the spatial distribution of the scattered light field of the metal aluminum target at any wavelength was simulated and analyzed. Secondly, the error of the theoretical simulation model was analyzed through the experimental data. Finally, the BRDF data at any wavelength were calculated using the simulation data and the experimental data with known wavelengths. The final results showed that at the 1064nm wavelength, the RMSE value of the calculated data obtained by this method is 0.3553, which is 0.2233 smaller than the RMSE value of the simulation data.This method is effective in calculating the BRDF of metal aluminum targets at different wavelengths.
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The importance and necessity of high temperature dynamic measurement techniques is analyzed in the paper. According to the requirement of solid rocket engine test, infrared radiation thermometry technology, colorimetric measurement technology and multi-wavelength radiation thermometry technology are used in the high temperature dynamic measurement device. The device worked well under harsh environment in the test site. Testing data is analyzed during the experiment and the results match the theoretical calculation. Application analysis of high temperature dynamic measurement techniques is made. It is clearly that optical measurement technology is quite prospected in the model test.
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Nuclear magnetic resonance gyroscopes(NMRG) have received widespread attention to the fields of national defense and civil applications due to their potential for miniaturization and low cost. The relaxation time is an important parameter to measure the performance of the alkali vapor cell of the NMR gyroscope, the most commonly used industry standard measurement method of longitudinal relaxation time(T1) is the measurement method using π pulse plus 1/2π pulse, so the measurement accuracy of the T1 is affected by the accuracy of the pulse duration. Usually the maximum value of the signal amplitude correspond to the time of 1 /2πpulse duration, but it cannot eliminate the influence of the random error of the system, the use of multiple cycles to automatically fit the pulse duration improves the accuracy of the pulse duration, saves a lot of measurement time, eliminates human error, and ultimately improves the T1 measurement accuracy.
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In view of the lack of space radiation benchmark traceable to the international system of units (SI), and the difficulty in establishing and maintaining the on-board traceability chain, we researched on the space cryogenic radiation measurement technology. The experimental prototype of the space cryogenic absolute radiometer was developed. The cage support structure is adopted to reduce the size and mass of the whole machine. The multi temperature zone cold aperture system was optimized to reduce of background radiation power and noise. The two-stage GM cooler is used as cold source, and provides the 20K working environment for the cryogenic absolute radiance detector. The thermal link of single stage heat sink was designed. Through active temperature control, a high stable thermal environment better than 1mk is established for the cryogenic absolute radiation detector. The fast measurement algorithm of the cryogenic electrical substitution measurement was designed, then the measurement period was shortened from 12 minutes to 4 minutes. The experimental results illustrate that: For the input energy of 4-15mw, the thermoelectric repeatability of the cryogenic absolute radiation detector is better than 0.01%. The repeatability of the experimental prototype for milliwatt laser power measurement reached 0.01%. The investigation results provide the thermal and experimental basis for the establishment of space cryogenic radiation benchmark. It is significant to improve the accuracy and long-term stability of earth radiance observation system.
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Infrared imaging seeker is the main direction of optical imaging seeker technology. Infrared imaging system determines the detection performance and tracking accuracy of the infrared seeker, and it is also the key factor for the miniaturization and lightweight of the seeker. Optical structure layout is the design key of infrared optical system. This paper introduces the traditional refractive, reflection, catadioptric optical system layout as well as the new off-axis reflection, hybrid refractive-diffractive, Kuder optical path, free-form surface optical form, and analyses its advantages and disadvantages from weight, volume, image quality, installation and debugging. Fairing is a key part of the optical system of infrared imaging seeker. It plays a high transmittance to the infrared band and protects the seeker from adverse external environment. This paper introduces the common materials of the fairing, the design of the fairing under hypersonic speed and the design method of the conformal optical system. The advance technologies of optical system design are introduced, including binary optics based on light wave diffraction theory, computational optics based on geometric optics, information optics and modern signal processing, micro-optics with great prospects for minimizing the seeker optical system, and adaptive optics which can overcome and compensate for the effects of atmospheric turbulence, and super lens technology using nanotechnology. This paper believes that the optical system of the future seeker should be based on the etching, material and surface design, and the technology of computational optics and signal processing will be widely used in optic design of seeker.
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In order to verify the performance of electro-optical products under the condition of large maneuver on the ground and further improve the tracking stability and accuracy of electro-optical products, the flight simulation test technology of large maneuver is studied. The characteristics of typical maneuvers are analyzed, and the motion simulation model which can realize the expected maneuvers is established. On this basis, the overall framework of the large maneuver flight simulation test system is constructed, and the test scheme is designed to verify the feasibility of the large maneuver simulation test system and the accuracy of the maneuver simulation model.
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This article starts with the development and progress of military technology and discusses the construction and development of unmanned combat. It can be said that unmanned combat is an inevitable trend in the development of military technology and modern warfare. In addition, the article focuses on the advantages of unmanned combat platforms and introduces the development status of foreign military unmanned combat platforms.
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In response to the needs of future multi-domain space fighting situations such as multi-platform, strong confrontation, clustering, Guidance, Navigation and Control (GNC) et. al, a robust navigation filtering algorithm with adaptive weight distribution is proposed. The algorithm breaks through the innovation measurement update method of the centralized satellite navigation system during the traditional integrated navigation, which is adapted by strapdown inertial navigation attitude, speed, position update and satellite navigation system innovation measurement. Combining the elevation angle of each tracked visible satellite by the integrated navigation receiver and the satellite signal carrier-to-noise ratio, it is carried out by real-time adjustment of the integrated navigation Kalman filter observation noise matrix and performing adaptive weight distribution of the observation equation. Updating the integrated navigation Kalman filter state equation and error covariance matrix is used by the satellite and inertial navigation pseudorange and pseudorange rate measurement values. Finally, the inertial device measurement error is corrected by the information fusion state results of the satellite and inertial navigation, which improves GNC system information fusion positioning accuracy and system robustness.
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At present, the technical research of lidar used in unmanned vehicle driving mainly focuses on continuously improving the density of lidar point cloud under the working mode of lidar with single wavelength, but the detection of echo is limited to single echo, missing a lot of details. Although the increase of laser point cloud density can improve the object recognition ability based on the geometric features of the point cloud, it also has a decreasing effect and many additional system requirements, which cannot fundamentally solve the problem of the lack of physical property detection ability caused by the single wavelength of lidar. To promote cross-country environment physical properties of the laser radar detection ability and help the laser radar's ability to obtain the information such as target state, in this paper, based on the calculation results of typical target spectral characteristics and lidar echo characteristics, a wavelength selection method for unmanned multi-wavelength lidar in off-road environment is proposed, which uses principal component analysis of typical target spectral features to determine the characteristic wavelengths that can distinguish the target by spectral features. Besides, the degree of waveform splitting is discussed through the simulation calculation of laser echo waveform, which helps finding the spectral wavelengths to distinguish targets in the same distance.
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In this manuscript, an acquisition platform for depth images based on Kinect V2 is designed, which can acquire depth images of the target model at any attitude angle (including view angle 0~80°, azimuth angle 0~360° and spin angle 0~360°). In addition, this manuscript implements a depth image recognition algorithm based on an integrated local surface patch (LSP). The algorithm first calculates feature points in regions with large shape variations, and then defines a LSP at each feature point, which is characterized by its surface type, the patch centroid, and the 2D histogram. Next, the potential corresponding patch pairs are found by matching two sets of LSPs, and the candidate models are obtained by the filtered potential corresponding patch pairs. Finally, the candidate models are validated by the iterative closest point (ICP) algorithm. Experiments are designed to validate the performance of the algorithm using multiple depth images with different attitude angles and occlusion ranges of eight military target models acquired by the platform. The results show that this depth image acquisition platform can provide rich data support for the design and verification of depth image recognition algorithms in the future.
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Using high-resolution remote sensing images for 3D modeling of urban buildings is widely common. However, the processing of shadows plays a vital role in 3D visualization, and the shadows in urban areas is more complicated. Hence, the research on shadow restoration is essential. The paper introduces the reconstructed DEM model data as prior knowledge, uses the characteristics of sunlight shadows and shadows in different channels for shadow detection, and finally proposes a shadow compensation method based on the Wallis filter principle and improved logarithmic transformation combined with shadow local enhancement, to compensate the detected shadows.
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Hardware in the loop simulation test technology of electro-optic system includes video injection technology and dynamic projection technology. Firstly, the dynamic infrared scene simulation technology is used to generate missile attack and complex jamming scene images; Secondly, the digital video is injected to simulate the front-end sensor and stimulate the integrated processor to detect and track the target; Finally, the large field of view medium wave infrared dynamic target simulator is used to build the missile threat environment to carry out the functional performance test of electro-optic system under the threat of single/multi-target attack. The experimental results show that the technology can build complex scenes according to the battlefield scenario, test the processing capacity of electro-optic system under the threat of single/multi-target attack, support the verification of search, acquisition, tracking and other performance indicators of electro-optic system, and provide support conditions for the development and debugging of core algorithms of electro-optic system.
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With the development of infrared dual-band focal plane detector in the field of engineering application, the research on image fusion algorithm of dual-band infrared thermal imager based on engineering application becomes more and more important. Because the human eye can only distinguish dozens of gray scales, but can distinguish thousands of color scales. At the same time, gray images can only store one-dimensional data, while color images can contain three-dimensional data, which expands the amount of information by tens of thousands of times, and is easier to be applied to the processing and processing of machine vision related work in the field of detection, search, recognition and tracking. Therefore the research on color image fusion is becoming more and more important. At present, color image fusion is the main development trend of infrared dual-band image fusion. The mainstream color image fusion can be divided into four categories: color mapping, color transfer, color lookup table and neural network. The above four algorithms are difficult to take into account the color richness, environmental adaptability and human eye observation comfort. In this paper, the above problems, this paper proposes a class on medium wave infrared and long wave band color map image fusion algorithms, the algorithm is based on each source image pixel and image mean differences, the differences between the information more reasonably map to color print, the final fusion image has a better image perception and environment adaptability, and preserve more details. A typical dual-band infrared thermal imager application Scene was selected, and the subjective image comparison and objective index analysis were carried out by algorithm simulation and other mainstream color fusion algorithms, which proved that the algorithm was effective and feasible.
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In this paper, the process and key technologies of infrared simulation are studied to meet the needs of infrared simulation of warships. Based on the knowledge of Infrared Physics and infrared radiation, the infrared radiation model of warship target and ocean background, the attenuation model of atmosphere to infrared radiation and the noise model of infrared detector are analyzed and established. Using JRM scene simulation software, the dynamic continuous infrared imaging simulation of ocean scene is realized, and the ocean environment, simulation band, noise effect and ship motion can be set. Through the construction of ocean scene infrared simulation system, it can effectively realize the real-time solution of complex sea infrared scene, and can be applied to the simulation research of anti-warship weapon scheme evaluation, sea infrared target tracking algorithm verification and so on.
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Single-pixle detector based computational ghost imaging (CGI) reconstructs an image by measuring the correlations between the scene and a series of masks. Recently, multi-pixels detector and parallel encoding is used to reduce modulation times and improve imaging speed. Due to the separate characteristics of encoding and detection in CGI system, detector defocus will not lead to image blurring in this single-pixel detector based CGI. However, detector defocus in multi-pixels detector based CGI is different to single-pixle detector based system. In this paper, based on the principle of CGI and the model of detector defocus, the influence of detector defocus in CGI is theoretically analyzed. Simulation and experiment results indicate that the multi-pixels detector based CGI inherits characteristics of antidefocus. The quality of reconstructed image is mainly affected by the degree of defocus and the array size of the detector.
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LiDAR echo intensity information can reflect the reflection characteristics of the target surface, and can be used as an important data source in the aspects of LiDAR point cloud image vision, classification and feature extraction. Geiger mode avalanche photodiode (Gm-APD) has the ability of single photon detection and high range sensitivity, and is widely used in the field of lidar. The number of statistics is often taken as the target intensity information obtained. In order to make the intensity image accurately reflect the reflection characteristics of the target surface, a kind of intensity information correction method of Gm-APD lidar is proposed. By eliminating the distortion caused by the detection model and target distance of the detector, the average reflectivity estimation error can be increased from 51.97% to 8.86%. Aiming at Gm-APD lidar, the determination method of parameters in parameter estimation method is systematically described in this paper. On this basis, the calibration of the laser emitter can improve the uniformity of the target, and the standard deviation is increased from 1.1818 to 0.0050. The proposed scheme can provide a reliable data source for target recognition, classification and feature extraction based on Gm-APD intensity image.
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An optimized broadband and high saturation uni-traveling-carrier photodiode is designed for optical communication system in this paper. The epitaxial layer is optimized by adopting linear doping in the absorption layer and inserting cliff layer, so as to obtain high speed and high saturation performance. According to comparing the performance of device with different thickness and doping concentration of cliff layer, the optimal epitaxial layer parameters are selected to reach the better performance. Theory and simulation study indicate that bandwidth and saturation current of the optimized device are 140 GHz and 120mA respectively, and dark current is 2 pA at 2V reverse bias.
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A new objective measurement method of minimum resolvable contrast (MRC) based on convolutional neural network (CNN) is proposed in this paper, in view of the fact that the subjective measurement results are easily affected by the observer’s subjectivity. Due to the low signal-to-noise ratio (SNR) of the low-light-level (LLL) images, it is difficult for traditional recognition algorithms to achieve ideal results, but the CNN can automatically learn features from the sample data for image recognition. This method does not depend on subjective judgment. It uses neural network instead of human eyes to recognize low SNR LLL images with different spatial frequencies and contrasts. The experimental results show that CNN is accurate and reliable, MRC images can be effectively recognized by it. The objective measurement of MRC based on CNN has good stability.
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Stereo vision plays an essential role in non-contact 3D measurement, which employs two cameras to achieve applications such as visual synthesis, terrain surveying, and deformation detection. The commonly used Scheimpflug principle is expressed as the object plane, the image plane, and the lens plane intersect in a line, based on which stereo cameras can be slantwise focused on the object space with an overlapping field of view and depth of field. Based on our previously proposed calibration method, a stereo-rectification of Scheimpflug telecentric lenses is proposed in this paper. The effectiveness and accuracy of the proposed methods are verified by experiments.
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In this context, the present research work aims at studying and developing an innovative approach for automated sampling path model for large simple regularly conical workpiece, which could provide designers easily and rapidly taken. Therefore, our attention is focused on 3D geometric relationships between neighboring end points of edge features of workpiece. An algorithm is proposed to guide the scanner device and move it along the main direction of the plane containing the projection of the next critical end point with the use of geometric properties of previously extracted end points. Thus, an appropriate 3D circular-arc scanning path is on-line automatically yielded step by step by an orderly collection of local connected end points. Finally, a series of experiment on typical conical workpieces are carried out to demonstrate the automated path planning technique and the final sampling quality.
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In recent years, 3D vision robot picking has been widely used in the fields of manufacturing, logistics, and warehouse due to its flexibility in handling various models. In this paper, we propose a robust and precise 3D vision guided robot picking method using multi-channel image information fusion. The major challenges are the failure or inaccurate of object localization and pose estimation caused by environment. Various considerations, we utilize a 3D camera based on binocular structed light to obtain the high accuracy RGB-D image with an additional customized illumination unit. In addition, we introduce the fusion method using multi-exposure control and multi-channel model from multi-color images to establish the reliable model matching for all conditions. Our system calculates the location and pose of the stove according to the rectangular template and the normal vector of the bottom surface to realize visual guidance. By projecting the point cloud onto the stove plane, only the height information is retained to generate a pseudo-image. Our 3D vision system reaches ≥99.8% successful pickup rate with the ±2mm accuracy along X, Y, and Z directions and±0.2°rotational accuracy along RX, RY, and RZ for both bare and painted surfaces under various illumination conditions during production. Our stove-picking systems installed in the welding and assembly stations improve the flexibility and the efficiency of the stove production line (100,000 unit/year).
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In this paper, a method of removing ion-feedback noise based on RPCA and median filter is proposed, a removal mechanism based on iterative strategy of "detection-location-removal" is established to remove the noise step by step, and BM3D algorithm is used to remove the Gaussian noise. The experimental results show that the proposed method can effectively remove the noise, and protect the edges and details of ICCD LLL images as much as possible. In addition, we quantitatively evaluate the denoising performance of the method. Our method obtains better objective measurement values. It has better effectiveness and robustness for ICCD LLL image denoising.
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The electron-multiplying charge-coupled device (EMCCD) is widely used in low-light-level (LLL) imaging field. In order to solve the problems of low signal-to-noise ratio (SNR) and low contrast of EMCCD LLL images under low illumination, a denoising method based on the nonlinear diffusion filter with wavelet transform and contrast sensitivity function (CSF) is proposed. Aiming at the problems existing in the P-M diffusion model, that is, the diffusion coefficient is easily disturbed by noise, and the direction affects the noise reduction process, the method introduces the wavelet transform and the CSF, then a new diffusion function is proposed to reduce the noise of LLL images. The experimental results show that, compared with other denoising methods, the proposed method has better denoising effect on EMCCD LLL images.
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Infrared images typically contain obvious dark-corner noise. It is a challenging task to eliminate such noise with the acceptable computation overhead and time overhead. In this paper, we introduce an effective dark-corner noise removal algorithm consists of two consecutive processing procedures. Firstly, in order to effectively filter dark-corner noise with as few as frames of infrared images, the proposed algorithm accumulates the low-frequency pixels during the several different frames of infrared images and eliminates the dark-corner noise by subtracting this parameter from the original infrared image. Then, this algorithm sets several detection windows for dark-corner noise to obtain another additive correction parameter and subtract this parameter from the original infrared image. We demonstrate the effectiveness of our algorithm from experimental perspective.
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Hyperspectral imaging is particularly useful for per-pixel thematic classification by unique spectral signatures of landscape materials. Deep learning techniques such as convolutional neural networks have boosted the performance of image classification. Recently, several composite learning-based convolutional networks, i.e., deep residual networks (ResNets) and dense convolutional networks (DenseNets), have been presented to learn deep feature representation for image classification, and achieve high classification accuracies. In this paper, we present a fairly comparable architecture, including two kinds of modified residual learning networks with a shallow depth using small training data. First, we perform the extraction of key components from deep residual networks and dense convolutional networks, which is a set of composite learning structures with skip connections. Second, the plain convolutional neural networks (PNets) have been constituted by a stack of plain blocks that also have been placed in the presented network architecture as the baseline networks. Third, we make them as comparable as possible with the plain convolutional network structures, so that the more profound exploration and improvement could be further done. Finally, we wrap them together and design a comparable architecture. Experiments demonstrate that the presented residual learning networks show special characteristics for hyperspectral image classification, which have not been revealed before.
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In order to improve the performance of low-quality noise grayscale image edge detection, using the principle that phase consistency is invariant to changes in grayscale and contrast, a noise image edge detection based on the fusion of multi-angle morphology filtering and phase consistency is proposed. The algorithm improves the defects of the previous edge detection algorithms that only rely on a single gray gradient difference or only use fixed direction weights and experimental results show that our algorithm is more accurate in noise suppression and edge detection of low-quality noise images than traditional algorithms.
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In this paper, starting from the noise and blur characteristics of the strain clamp X-ray image , an image processing method combining bilateral filter denoising and unsharp mask enhancement is proposed. Experimental results show that unsharp mask algorithm have certain limitations in image edge enhancement. After the image is denoised by bilateral filtering,the unsharp mask method is used for image edge enhancement, which can effectively expand the scope of the unsharp mask algorithm. This method greatly improve the image qualityand help identify defects. It provides a strong guarantee and support for the X-ray inspection of the strain clamp, and has important practical value.
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In the bionic curved compound-eye camera (BCCEC) we have invented, the overlapping field of view (FOV) among the ommatidia makes 3D detection possible. In this work, we analyzed the overlapping FOV in BCCEC in detail to prove its potential in 3D detection and designed a new experiment to test its performance. In that the FOVs of multiple ommatidia in BCCEC overlap each other, the FOV of a single ommatidium is used as a representative analysis. The relationship between the overlapping ratio of FOV and the object distance is quantitatively calculated. The results show that more than 95% of the FOV can be 3D reconstructed when the object distance exceeds 32 cm. Next, in order to realize the automatic calibration of all ommatidia, ommatidia are numbered and an addressing algorithm based on the number information of ommatidia is designed, which can be used to determine the adjacent ommatidia of any ommatidium so as to acquire the ommatidia pairs that need to be calibrated. Then, since the aperture of ommatidium is relatively small and it is difficult to accurately align, a new 3D detection experiment is designed. The laser rangefinder is fixed, the black paper is used to block the laser and the formed light spot is used as the detection target. The experimental results show that 3D detection can be performed in the whole FOV of BCCEC. The BCCEC can obtain multi-dimensional information in a large FOV, and it have greater application potential in obstacle avoidance and navigation.
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3D printing technology is becoming more and more mature, and it is widely used in aerospace, chemical industry, automobile and other fields. Silicon carbide has a series of excellent physical properties such as high elastic modulus, moderate density and good stability. In order to make the space remote sensing camera break through the limitations of traditional processing technology and design ideas, it can further improve the lightweight rate, obtain better force stability, and reduce the demand for the whole satellite resources. In this paper, silicon carbide is used as raw material and 3D printing technology is used to develop space remote sensing camera. Firstly, the advantages and characteristics of 3D printing technology and printing materials are introduced. Then, according to the particularity of the technical characteristics, the methods of using 3D printing technology to design space remote sensing camera are summarized. Then, according to the design method, the design, simulation and optimization of the remote sensing camera structure are carried out. Through the mechanical test, it meets the design expectation.
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The PID controller is widely used in two-axis photoelectric platform velocity loop, however the control precision and the stability of controller are contradictory, especially when friction torque is added. In order to solve this problem, the characteristics of PID controller were analyzed detail in this paper, then a sliding mode controller was designed based on the approach law. First, the model of two-axis photoelectric platform velocity loop was established, then the friction model was linearized according to the interval analysis theory, after that the sliding mode function and the controller was designed, next the simulation model was build, finally, the performance of the velocity loop was compared between sliding mode controller and PID controller, the results showed the sliding mode controller has higher control precision and the stability.
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Acquiring the identity information of the ships passing through the canal and the sea automatically by intelligent equipment is helpful for the water transportation department to strengthen the management and is meaningful for the construction of the urban intelligent traffic management system and national defense security. However, this is challenging due to complex ship profile, ship license background and object occlusion, variations of ship license plate locations and text types. This paper proposes a backend service system for ship detection and plate recognition based on Yolov4 and PaddleOCR, and produces a dataset containing 54059 pictures. By setting up a Socket server, the system receives the image information sent by the front-end, uses the YOLOV4 target detection algorithm to identify the ship and locate the ship plate, and simultaneously uses the PaddleOCR character detection and recognition algorithm to locate and identify the characters in the image. After frame synchronization and data fusion of target detection result and character detection and recognition result, the result is transmitted to the front-end through Socket. The system can be deployed on Win10, Linux and embedded system, working reliably with high precision to meet the practical application.
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This paper introduces a method for calculating the thickness of thin films by means of transmittance spectrum, especially the ones deposited on the glass substrates. The film thickness iscalculated by this method and compared with the results measured by probe testmethod, the errorsare less than 3%. Compared with the past ones, this method does not need to peel off the substrate and thin films, does not destroy the surface of thin films, and can detect the smoothness and thickness of thin films at any time. It can be widely used in industrial films deposition to improve the production and efficiency.
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The ultraviolet radiation of the missile plume is an important target for the space-based UV warning system, but its intensity is several orders of magnitude weaker than the infrared radiation. Therefore, the detector used to detect the ultraviolet radiation of the missile plume must have the characteristics of high sensitivity and low noise in order to detect weak signals. At present, the imaging detector used in UV detecting systems is mainly vacuum device, which has the advantages of UV sensitivity and high gain, but its quantum efficiency is low, generally 10% - 20%. Meanwhile, due to the vacuum and high voltage working conditions,the device is easy to be affected by space radiation and the service life of the device is very short. In addition, for vacuum device ,the spectrum range is narrow, which limits the application field of the detector. At the same time, the current vacuum devices can not work in the strong solar background, and it needs to use the composite filter components with small caliber and large thickness. Consequently, the field of view and the efficiency of the optical system are limited, which seriously affect the performance of the space remote sensor. In this paper, the research of high efficiency UV imaging detector based on spectral conversion is carried out. The efficient conversion and detection from ultraviolet to visible light can be realized by using the combination of down conversion light materials and large array visible light charge couple device (CCD) through special technology.Firstly, in order to meet the requirements of optical conversion materials and coupling technology, the composition and system selection of photon conversion nanomaterials are completed by using the theory of rare earth spectrum. Secondly, the coupling process design is carried out, and the advantages and disadvantages of spin coating and thermal evaporation are verified by experiments. The coupling between materials and devices is realized, and the quantitative measurement method of quantum efficiency is given. On this basis, the down conversion UV camera is developed to verify the in orbit technology, and the in orbit image is obtained, which proves the feasibility and effectiveness of the down conversion UV detector technology.
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A high-speed real-time structured light imaging system is presented in this paper. The improved linear structured light imaging method is transplanted to the FPGA hardware system, and the imaging frequency is greatly increased. The best imaging effect can be obtained when imaging objects with different reflectivity. Experiments show that this method can achieve outstanding imaging effect for complex objects, and the imaging frame rate can reach 60 Fps.
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In a smoke environment, the laser is susceptible to be scattered and absorbed by smoke particles, which in turn affects the detection performance of the pulsed laser fuze. Combining the analytic hierarchy process and the fuzzy evaluation method, this paper establishes the evaluation system of the target layer, the criterion layer and the index layer. The fuzzy evaluation criteria of each index are given, and combined with specific examples, the backscattering characteristics of pulsed laser fuzes in smoke environments are evaluated, and the evaluation results of backscattering characteristics under this example are obtained. A basis can be provided by the paper for the use of pulsed laser fuzes in smoke environments.
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Current lens-based optics is limited in dimensions and shapes due to the fabrication process. With the development of 3D lithography in recent years, the polymer-based lens fabricated by direct laser writing based on two-photon lithography shows unique capabilities compared to those fabricated by traditional methods. It shows advantages such as fast writing speed and high resolution. However, for those tiny delicate structures such as resonators and waveguides, the quality will be losing if the speed is too high, besides, it costs time to fabricate large structures. In this paper, we present a promising three-dimensional microfabrication system based on single-photon polymerization using a digital micromirror device with a UV light source at 390 nm. The designed system has a high resolution and it needs shorter time for fabrication. Here, the lenses with different sizes and curvatures are fabricated directly on a single mode fiber tip, for optical fiber imaging system. The paper presents experiment-details of the design of the single-photon polymerization system, fabrication the optical components on optical fiber tip and the results for imaging applications. We demonstrate the optical design and manufacturing using a DMD-based 3D printer for potential applications for optics, fabrication of biosensor and imaging.
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Road traffic sign is critical in informing people of the traffic situation and restricting drivers’ and pedestrians' behavior. Therefore, the real time autonomous detection and recognition ability of road traffic signs play an important role in fields such as navigation for the blind, driver warning system, and vehicle assisted driving. This study employs lightweight neural networks based on MobileNet and Yolo-V4 and compares their recognition speed and accuracy. The experimental results show that YOLO-MobileNet-V2 and YOLO-MobileNet-V3 had high recognition speed but lower accuracy. YOLO-V4-tiny and YOLO-MobileNet-V1 presented high accuracy, with mean average precision (mAP) of 90% or higher, while maintaining the detection speed over 60 frames per second (fps), meeting the real time standard in road traffic sign recognition. The study proves that YOLO-V4-tiny and YOLO-MobileNet-V1 can be employed to reduce the time of calculation and lower the requirement of hardware equipment by reducing the computational complexity. There-fore, this study provides certain practical reference in related fields.
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As the development of electro-optical weapon system, the technique of multi-sensor is used popular. A visual telescope based on a television viewing-aim system has been designed in this paper, which has the common aperture. The optical system which used visual telescope as optical reference of correcting the optical axis, share the same objective and compound prism, and has been applied to versatile optic-electronic observation with coating beam-splitting film on inclined plane of the block prism. A visual telescope system has been presented, which has been inverted image with a Schmidt roof-prism. As a result, a visual telescope could be used to aim target by the eye at exit pupil, which magnification is 10×, field of view is 5°,exit pupil isφ6mm, exit distance is not less than 20mm, the optical resolution is not more than 5″.There is a very important point, that compound prism has been applied in visual telescope optical system, which cause not only reversed image but also turned 45°optical path to meet the requirement of man-machine. Furthermore, owing to high resolution and maximum probability of distinguish, a CMOS digital camera based on cameral link has been used in the television viewing-aim system, which resolution is 1024× 768, the pixel size is 4 μm. So a television viewing-aim system is made up of telephoto objective to shorten optical length, which has F number 4 and 1°×0.75°field of view in near infrared wavelength. And the system could be used to detect, distinguish and aim target by getting reflect characteristic of the target and converting video image in real time. Finally, according to the analysis of tolerance, the fabrication and assembly tolerance are has been formulated, the result could meet the imaging demands.
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Curved detectors have attracted more and more attentions and gradually become a focus research area due to the widespread applications of the optical imaging technology in the past few years. Unlike the traditional planar detectors, curved detectors have focal planes that can be bent into the same shape as the image surface of the optical system theoretically. As a consequence, the field curvature is directly suppressed as we don’t need to flatten the focal surface to fit a plane detector, leading to a simplified optical system and a better performance, especially suitable for optical imaging systems in space applications. However, due to the intrinsically planar nature of the established fabrication technology, it is extremely difficult to achieve these innovative detectors. In this paper, we summarized the latest works about curved detectors and proposed a novel type based on graphene/QDs. The device consists of a graphene/QDs film interconnected with a conventional readout circuit via a curved SiO2 substrate. A critical important design feature is the Au lines within the high depth-diameter ratio holes of the substrate, through which the graphene pixels are connected to the readout circuit. Compared to the published methods, the fabrication process of this detector is simplified, and the cost budget is reduced as well. More importantly, this detector can achieve a superior performance thanks to the prominent properties of graphene/QDs. We believe that our new device concept will stimulate the flow of ideas and contribute to the mature applications in the future.
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Infrared imaging generally refers to the technology that takes radiation energy of the target itself as received signal and converts it into an image. We can obtain geometric characteristics as well as temperature characteristics of the target day and night by applying the infrared imaging technology as it can hardly be affected by illumination conditions and adverse weather, hence it is extremely important for both military and civil use. Since the combination of infrared and visible light imaging enables us to achieve the target information more comprehensively, the remote sensing cameras rapidly accomplished the transition from single pass to multipass, which allows them to obtain visible light and infrared images through different optical paths simultaneously. However, this imaging system greatly increased the volume, mass, power consumption and cost budgets. Here, we discussed an innovative graphene/QDs photodetector for remote sensing. As the bandgap of QDs is controllable through its size-dependence, its response spectrum could easily be modulated through the size control and ligand exchange1, thus enables us to obtain a detector with response spectrum range from visible light to medium wave. And with the help of PMMA-assisted transfer processing2, we can arrange the QDs with different response spectrum on purpose. Therefore, it is possible for us to customize the response spectrum for each pixel, and this truly enables the visible infrared integrated single pass imaging system and could generate a variety of strategies for remote sensing.
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Obtaining a clear image of the underwater environment with classical imaging methods is still a challenging task due to the large amounts of noise caused by absorption and scattering nature of water and complex light interactions. By contrast, ghost imaging (GI) is a second-order correlation imaging technique, which has the disturbance-free ability in severe backscattering and high absorption conditions. In this paper, a physical model of three-dimensional ghost imaging (3DGI) through turbid water was set up based on laser detection and ranging (LADAR) and GI system, which considering the light-field transmission, the effects of absorption and scattering of water and the interaction between light field. Then the quality of 3DGI with different turbid water conditions and over different propagation distances was investigated by numerical calculation. The results show that the proposed 3DGI scheme is capable to reconstruct the object of long-distance in highly turbid underwater environments, and the reconstruction quality is closely related to the turbidity of the water and transmission distance. This work provides a reference to underwater 3DGI application, and maybe a better alternative strategy for underwater imaging.
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Because of the obvious deformation difference for the alkali resistant glass tubes with different internal stress, in this paper, a new method for evaluating the internal stress and annealing quality of alkali resistant glass tubes based on digital image correlation algorithm is proposed. According to the deformation change rate of alkali resistant glass tube that obtained by digital image correlation algorithm, it can directly determine whether the internal stress meets the production standard. The alkali resistant glass tubes which have undergone abnormal(annealing time less than 5 hours and annealing temperature lower than 630 ℃) and normal annealing operation were selected as samples of experimental group and control group. The samples of these two groups were heated to 200 ℃ and then cooled to room temperature. The displacement fields between deformed images and the initial image are calculated by digital image correlation algorithm and the mean values change rate of the displacement fields are regard as the evaluated basis for the internal stress and annealing quality. Since the new method has many advantages such as simple, efficient and non-contact and only two continuous pictures are required in the detection process, it has been applied in the actual industrial production testing. In addition, this method provides a new approach for the internal stress detection of other solid materials.
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Aiming at the control, display and processing requirements of the portable active and passive imaging detection system, based on the software modularization idea and the hardware architecture of the system, the imaging detection control and processing software is designed and implemented.Through the analysis and explanation of the basic principles, basic structure, software architecture and functions of the system, it is demonstrated that the software has the advantages of complete functions, good human-computer interaction, simple operation, and efficient operation.Finally, the system is used for imaging detection experiments. The results show that the software can acquire, process and display image data in real time, and can accurately adjust various system parameters, which can well meet the application requirements of portable active and passive imaging detection systems.
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For special tasks such as disaster rescue, urban security and anti-terrorism investigation, due to the complex environment and task scene, UAV is often used to complete the tasks. Based on the requirement of special UAVs in these kinds of special mission environment, this paper designs a special UAV with three capabilities of flight, ground moving and wall climbing. The triad UAV adopts the flying wing aerodynamic layout. Through the comprehensive optimization design of material, layout and control, it has the characteristics of simple structure, light weight, convenient control and rapid deployment. It has strong adaptability to special mission environment with high risk, narrow operation space and need to be concealed and intruded, so it is very suitable for special missions.
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Infrared and visible image fusion can obtain an integrated image containing obvious object information and high spatial resolution background information. Therefore, combining the characteristics of infrared and visible images to obtain the fused image has important research significance. In this paper, an effective fusion algorithm based on non-subsampled contourlet transform (NSCT) is proposed. The method is based on the application of a modulated pulse-coupled neural network fusion (PCNN) strategy and an energy attribute fusion strategy in the NSCT domain. First, NSCT is used to decompose the input original image into low frequency sub-images and high frequency sub-images. Then, the high frequency sub-images are fused via a multi-level morphological gradient (MLMG) domain PCNN and the low frequency sub-images are fused via the energy attribute fusion strategy. Finally, the fused sub-images are reconstructed by inverse NSCT. Experimental results demonstrate that the proposed algorithm has a better fusion performance in both subjective evaluation and objective evaluation.
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High-precision and long-range absolute distance measurement is a vitally important topic in large-scale metrology, and it has broadened applications in the manufacturing industry. Especially, the dual-comb time-of-flight distance measurement is a promising method combining with the advantages of fast speed and high accuracy. The measurand would be determined by asynchronous optical sampling (ASOPS) methods with a slight difference in repetition rates. Here, the home-built optical platform of the Er-fiber femtosecond frequency combs would be introduced with a repetition rate of around 200 MHz and carrier-envelope offset frequency of 20 MHz. Besides, the strategies of precision enhancement for dual-comb time-of-flight distance measurement with nonlinear intensity detection are discussed by the numerical simulation. The sampling interval could be optimized by choosing a proper range of repetition rate and difference of repetition rates. A fine curve fitting method is also proposed for further precision improvement. The results of numerical simulation would provide a valuable reference for the experimental process.
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During servicing of subsurface transportation pipelines, axial pressure generated by high-temperature and high-pressure working conditions is released through upheaval buckling deformation. When the overall deformation of the pipeline exceeds limits, the weakest part of the pipeline will suddenly break and fail, causing serious economic losses and social problems. To ensure safe pipeline operations, it is necessary to monitor the upheaval buckling mechanism of pipelines with a new type of monitoring technology to realize structural reliability assessment under complex loads. Based on Brillouin optical time-domain analysis (BOTDA) distributed optical fiber sensing technology, this study proposes a method to identify buried pipelines’ structural state to solve the problem of detecting upheaval buckling with initial defects under unknown loads. Based on the BOTDA principle, the proposed method comprises a distributed structural response monitoring approach for pipelines. The Euler-Bernoulli beam deflection curve calculation method is used to establish a pipeline buckling displacement reconstruction algorithm to quantitatively identify the occurrence and development of pipeline upheaval buckling. The initial-defect buried pipeline model test is used to verify the feasibility of the proposed method. The results show that the proposed method for identifying the upheaval buckling of buried pipelines can realize quantitative identification of front and back buckling behavior of submarine pipelines under unknown loads, which has important practical significance and application value.
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To realize the fast, high-quality alignment of off-axis reflective system, a computer-aided alignment method based on high-precision extraction of optical axis and high- precision restoration of surface shape of off-axis mirror was proposed. The optical axes of the mirrors are derived by means of a zero-position compensation detection path of the off-axis mirrors, and accuracy is better than 6", realize more rapid and accurate system initial alignment. There propose a surface shape data conversion algorithm, combined with Code V, it can realize the high-precision restoration of measured surface shape data of off-axis mirror in simulation, accurately calculate and separate the influence of shape error and position misalignment on system quality, and realize the fast and high precision alignment of off-axis reflective system. This method is applied to the practical alignment of one off-axis TMA system, wave aberration RMS≤0.084λ(λ=632.8nm) after initial alignment of the system. After only once calculation and alignment, full field RMS≤0.055λ. The experiment results demonstrate that this method is feasible.
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Wigner distribution function (WDF) is a complete representation of the optical field with arbitrary coherent state and can be regarded as a local spectrum. It has unique advantages for representation, measurement and manipulation of partially coherent fields. Image sensors can only obtain the two-dimensional intensity data, which is the shearing projection of WDF. The shearing of WDF, which equals to the propagation of optical field, embodies the coherent properties of optical field. In this paper, a phase space retrieval method based on three-dimensional (3D) intensity focus stack combined with an iterative optimization is proposed. WDF with arbitrary coherent state can be reconstructed by 3D intensity sequences, which can realize the local spectrum retrieval and the analysis of spatial partially coherent fields.
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Real-time detection of object is a hot topic in remote sensing applications. In this field, deep network has shown large potential in terms of accuracy. However, it is difficult to design a lightweight hardware and software system to satisfy the satellite edge deployment due to the complexity of the structure of deep network, large amount of computation and high demand for computing resources and storage. In this article, we propose a lightweight object detecting system, based on MPSoC FPGA processor, to solve the problems. First, the lightweight algorithm for object detection which is suitable for the deployment of satellite edge devices is studied. Then, to reduce the number of parameters and the overhead calculation and storage, a network parameter compression algorithm based on dynamic mapping is laid out. Finally, a prototype verification system based on MPSoC FPGA processor is constructed to realize aircraft object detection. The experimental results highlight that the accuracy of detecting the aircrafts can reach more than 92%. For single frame image with input size of 416×416, the reasoning time is reduced to 7ms, suggesting that the requirement of real-time processing of remote sensing target detection can be met.
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Cameras capture every pixel in transient duration for one frame image, while lidars capture every point in relevant long duration for one frame point cloud. When lidars stay static, point cloud will not cause motion distortion, when lidars move, point cloud will have motion distortion, this issue becomes worse with the increase of lidars’ linear velocity and angular velocity. As an inertial space movements’ sensor, IMU (inertial measurement unit) captures motions by a high frequency, which can be utilized to correct lidars motion distortion. In this paper, a variable motion model to correct lidars motion distortion is proposed. Comparing to the constant motion model, the proposed model has better performance on handling distortion caused by varying motion. Experiments results show that the variable motion model has a beneficial influence on distortion correction.
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The existing space situation awareness optical imaging system is limited by the satellite platform and optical system, and it is difficult to realize large aperture observation and multi-dimensional optical characteristics data acquisition for rapid target detection. Aiming at the problem that the sparse aperture system is difficult to achieve clear imaging in all depth of field, and the image quality degradation caused by the defocusing and dislocation of the object point and phase closure, the refocusing imaging technology based on light field modulation is adopted to expand the synthetic aperture to full depth of field, and effectively compress the amount of data.
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A novel fiber optic gyroscope with low coherence laser as driving light source is designed in this letter, the low coherence laser has higher average wavelength stability and lower relative intensity noise which is achieved by using Gaussian white noise phase modulation to broaden the linewidth of a DFB laser. The scale factor stability of FOG can be effectively improved when applied to FOG research.
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Wide field-of-view (FOV) and high-resolution (HR) imaging systems have become indispensable information acquisition equipment in many applications, such as video surveillance, target detection and remotely sensed imagery. However, due to the constraints of spatial sampling and detector processing level, the ability of remote sensing to obtain high spatial resolution is limited, especially in the wide FOV imaging. To solve these problems, we propose a multi-scale feature extraction (MSFE) network to realize super-resolution imaging in a low-light-level (LLL) environment. In order to perform data fusion and information extraction for low resolution (LR) images, the network extracts high-frequency detail information from different dimensions by combining the channel attention mechanism module and skip connection module. In this way, redundant low-frequency signals can pass through the network tail-ends, furthermore, the more important high-frequency components calculation can be focused. The qualitative and quantitative analysis results show that the proposed method achieves the most advanced performance compared with other state-of-the-art methods, which shows the superiority of the design framework and the effectiveness of presenting modules.
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Remote sensing, as a rapid and large-scale investigation and monitoring technology, widely used in the study of lake evolution and dynamic changes. In general, the evolution of lakes in the arid area is obviously controlled by the distribution of groundwater system. Based on high-resolution satellite data, this paper obtains, the elevations and boundaries of 124 lakes in a long time series in the Badain Jaran Desert region, and summarizes the pattern of, lake evolution and shrinkage. Besides, the division of the groundwater system in this region has been achieved, by estimating the water volume changes in the two periods, and the analysis of the regional geological structure characteristics. The application results show that over the years, the average elevation of the lake has decreased by 8.79m, the cumulative shrinkage of areas have reached 64.81 km2, and the total volume of lakes has been reduced by 465 million m3. The spatial differentiation characteristics of the shrinking lakes are obvious, and the difference in the extent of lake shrinkage is significantly controlled by the regional tectonic basement, which indicates that the regional groundwater system may have a local nested structure. Based on remote sensing method, the groundwater system in Badain Jaran Desert is divided into two primary units in the north and south, and four secondary units in the south.
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Images store a lot of information and are the window for human beings to understand things. A lot of research is devoted to analyzing and processing images, which is called image processing in a broad sense. Image processing includes image recognition, image restoration, image enhancement, image coding and so on. This paper mainly focuses on the field of image restoration. Image restoration, also known as image inverse problem, aims to restore high-quality original images from degraded or damaged observations. It also acts as a preprocessing step in many intermediate and advanced image processing tasks. Due to the limitations of sensors or environmental conditions, imaging systems usually have factors such as noise, optical or motion blur, resulting in image degradation and distortion. Aiming at the ill posed problem of image pixel missing and blur in the process of compression coding, this paper uses GMM model to solve the degraded image, so as to achieve the purpose of image restoration.
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When infrared imaging-guided aircraft is flying at high speed, the optical dome is heated strongly aerodynamically and generates infrared radiation, which forms background noise on detector, which reduces target detection performance.In order to research the influence of the continuous high dynamic change of temperature of the dome on infrared imaging, the fluid thermal solid coupling calculation model of the dome under the trajectory is established, and the time-varying non-uniform temperature field of the dome is obtained. The aerodynamic thermal radiation distribution on the detector is obtained by ray tracing, and a simple method of solid angle discretization is proposed for reference.The results show that the temperature of the dome reaches the maximum value of 417.6 K at the end of flight, and the irradiance of the image plane reaches the maximum value of 0.8791W/m2. The signal-to-noise ratio(SNR) and contrast gradually decrease with the flight time. When the target is located in the background gray-scale slope area, the SNR drops the most that drops by 66.77% compared with the reference image without aerodynamic heating at the end of flight. Contrast decline is basically independent of the location of the target, and the end time drops by 93.42%. The simulation method of aerodynamic thermal radiation and the evaluation method of degraded image quality proposed in this paper have a certain reference significance, which lays a foundation for the optimization of response wave band of infrared detection system and the suppression of aerodynamic thermal.
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In this paper, a novel method for measuring the projected area of complex 3D objects based on lidar point cloud data is present. To solve the problem of partial data missing in the process of collection, a method of combining Moving Least Squares (MLS) and greedy projection triangulation algorithm for 3D surface reconstruction is proposed. Combined with the MLS method, the problem of greedy projection triangulation method that it requires the point cloud density to change uniformly is made up. The surface data obtained by this method is smoother and the number of holes is reduced, so that the final projected area calculated is much more accurate. The point cloud display platform is written in C++ under Win10 environment. We select PCL to render point clouds and grids and use VTK framework to implement visual interface, which can display the algorithm results of this article.
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The original point cloud data acquired by 3D scanning equipment has a large number of noise points, which will seriously affect the subsequent work such as point cloud alignment and surface reconstruction. To address this problem, we propose a point cloud smoothing and denoising algorithm based on the local neighborhood change factor. The algorithm classifies the noise in the point cloud into singular and non-singular points according to the magnitude of the surface change factor of each point. For singular points, the improved median filtering algorithm is used to correct the singular points; for non-singular points, the density difference function is introduced in the bilateral filtering algorithm and smoothed by using the improved bilateral filtering algorithm. The smoothing and denoising experiments are conducted for different data models. The experimental results show that the method in this paper can effectively remove the point cloud noise and smooth the point cloud surface while preserving the detailed features of the point cloud. Compared with the bilateral filtering algorithm, the algorithm in this paper is both maximum error and the average error are reduced.
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In order to detect weak magnetic field, the demonstration based on all-fiber full polarization Sagnac magnetic sensor was used in our scheme. Beam condense system(BCS) is very meaningful as one of the key technologies in this magnetic sensor. In the paper, we introduce a simple way to design a BCS. Because of the restriction of the system space, the BCS can’t take too much space. However, the common product of beam condense system is kind of complex and will take much space, these disadvantages can’t meet the application. We choose small lenses, design the simple workpiece by ourselves and coupling into our detection system. The workpiece including pressure rings and sleeves. In our plan, we choose telescope system as optical path. After passing the beam condense system, the diameter of beam can be smaller and reflect in magnetic-optical crystal (MOC) many times. In this way, the sensitivity of detection system can be magnified for about 11 times. Overall, the most obvious advantages of this beam condense system are simple structure, small space and low cost. There are two important parameters of beam condense system: The first is called condense ratio, which can be controlled by the choice of lenses. The second is called final beam diffusion angle, which depended on both the condense ratio and beam diffusion angle of collimating lens.
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Structured light 3D reconstruction technology has the advantages of non-contact, low cost and high reliability, and is widely used in industrial parts defect detection, cultural relics 3D digitization and other fields. As the core part of structured light, coding method is the key element to obtain 3D scene information, which directly affects the accuracy of 3D reconstruction. The combination of gray coding and phase shifting is a typical method for 3D shape measurement. However, due to the complexity of sinusoidal fringe calculation, and the fringe pattern boundary cannot be strictly aligned, there is a step change problem, which limits the application of this method in the field of real-time high-speed three-dimensional measurement. In this paper, the phase shift method of triangular wave and gray coding are combined to measure the 3D morphology. The triangular wave function only uses two raster images and the phase information can be obtained by simple intensity ratio calculation. The binary defocus technique can shorten the projection time, but it blurs the edge boundary of gray code and aggravates the step problem of reconstruction of object surface. In order to solve this problem, the complementary gray code whose fringe width is half of the sinusoidal fringe period is used to correct the period deviation. The experimental results show that the proposed method can reduce the number of fringe projection, simplify the calculation steps and shorten the time of data processing, so it is feasible.
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The rapid development of modern science and technology puts forward higher and higher requirements for displacement measurement. As a non-contact measurement technology, laser ranging has played an important role in various fields for the unique advantages and has become a hot topic in the field of measurement research. At present, there are little research on high-precision displacement measurement at medium and long distance, the needs of which are widespread in practical application, so this work has important value. Among various laser ranging technologies, the laser triangulation method has the advantages of high-speed, high precision, simple structure, etc. Therefore, this paper chooses the direct laser triangulation method to carry out the research after analyzed the common types of laser triangulation system. In view of the requirements of high-precision displacement measurement requirements at medium and long distance, this article discussed the design of laser triangulation measuring system and the selection of structural parameters. Then we proposed a direct laser triangulation measurement structure under Scheimpflug conditions. This system selects PSD displacement transducer to collect the position information of the scattered light spot. After that, this paper discusses the principle of laser triangulation distance measurement and simulates the system. Then the influence of different parameters on high-precision displacement measurement and the relationship between them are investigated. Based on the research talked above, we got a set of structural parameters of the displacement measurement system. The measurement accuracy can be ~micron with the working distance of 500mm.
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Quantum signature is used for verifying authenticity, integrity, and non-repudiation of message in communication. Many different quantum signature are proposed, however, almost all of them merely work under the assumption of ideal conditions. At present, the non-idealities in the actual system have attracted great attention of researchers, and they are constantly exploring how to overcome or reduce the adverse effects and constraints. However, the existing results have not thoroughly revealed the problem of "how inaccurate quantum physical operations affect and restrict the performance of quantum communication", which is the point of this project. In this paper, the description of imprecise quantum physical operation is proposed, the fidility of quantum blind signature with imprecise quantum measurement is discussed. Finally, our results show that the phase paremeter Φ and Φ ε has no effect on the fidelity of quantum blind signature and the higher fluctuation of impercise quantum measurement parameter, the lower fidelity will be. We hope that the results of this study will help improve the ability of quantum blind signature experiments in actual quantum systems to resist the influence of inaccurate measurements.
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This paper proposes a method for extracting the solar centroid based on a multi-color model. The method is based on the three-color models (Lab, HIS, RGB) to segment and extract the color features of the image at the same time, coarsely locate the existence area of the sun target, and filter the obtained results through shape features, etc. We should try our best to optimize algorithm, for which can obtain a precise sun image. It is very important to combine circle center fitting with edge extraction to obtain the coordinate of edge point. What’s more, we need to select the edge points to form a sample set of edge points. It is helpful to fit the center of the circle by the least square method. The algorithm is improved to find the center of mass of the sun. By subjective judgment and error analysis evaluation of a large number of results, this method is useful as we expecting for the segmentation and extraction of solar targets. But due to the interference of the shooting angle, light, exposure, weather and other factors when the image was taken, which makes the result of target segmentation not ideal. However, it has little effect on the final centroid extraction result.
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This paper has fabricated and characterized a bilayer SPR optical fiber sensor, enabled by hydrogen doped molybdenum oxide (HMO) nanodisks coated on the metal film's surface. Doped molybdenum oxide with ultra-doping and large permittivity properties can tune the plasmonic absorption in a visible region. The materials were synthesized by hydrothermal method, characterized by the atomic force microscope, Raman spectroscopy, and other analytical instruments. The electrical and optical properties of the materials are calculated and analyzed with density functional theory (DFT). The sensor measured the refractive index of a liquid solution, and a sensitivity of 2565 nm/RIU was achieved, which was approximately 1.4 times higher than that of a conventional SPR sensor without modification HMO nanodisks.
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The spectral absorption characteristics of hemoglobin determine that the contrast between R and B components in the white light endoscopic blood vessel image is poor, and the blood vessel features in the G component are the clearest and the contrast is good. Based on this feature, this paper proposes to use the G-component image to perform nonlinear stretching to obtain the stretched image, and subtract the original image from the stretched image to obtain the G-component high-frequency detail image containing blood vessel feature information; Then, using the high-frequency detail image to perform unsharp mask processing on the R, G, and B components of the original image, respectively, to obtain a blood vessel contrast-enhanced image; In order not to cause grayscale dispersion in the transition zone of the blood vessel edge during stretching, Performance simulation experiments are carried out for endoscopic images of fundus and oral cavity. The results show that the proposed algorithm not only improves the image contrast, but also has a better enhancement effect on small blood vessels with inconspicuous original features. By comparing with the performance of Spectra B and the method of literature [6], the average gradient value of the algorithm in this paper is increased by about 300%, the information entropy value is increased by about 30%, and the DV-BV value is increased by about 75%.
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Remote sensing image combines the characteristics of visible light image, infrared image and other multi-spectral images, making it rich in details and low resolution. However, due to factors such as weather and transmission errors, salt and pepper noise is prone to occur, and it is difficult to effectively detect weak edges. Aiming at the problems, a morphological edge detection algorithm based on hierarchical multi-scale is proposed in this paper. Firstly, the adaptive median filter is used to smooth the remote sensing image. Secondly, it is proposed to use the mutual information of images as the cost function for processing, and the multi-scale hierarchical ratio is 2 1 . Then, the four directional structural elements of 0 , 45 , 90 and 135 are used to extract the original-scale and small-scale image edges respectively. Calculate the sum of the gray difference values of eight neighborhoods of the edge points, thus calculate the direction adaptive weight, and then the edge detection results are obtained by fusion respectively. Finally, the pixels in the edge image are classified, and the fusion method of enhancing edge and weak edge and filtering false edge is proposed, and then the edge detection image is obtained. Aiming at the application of remote sensing images, the comparison of the results shows that the proposed algorithm has stronger anti-noise performance, the weak edge detection ability is improved, thus avoiding missed detection and false detection of edge information, and detecting more complete and accurate edge details.
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The present paper is a study of laser Schlieren technique and its applications in kinds of flows from subsonic flow to high speed. Laser Schlieren technique has been investigated recently, which emitted 20mJ laser pulses at 5Hz. Owning to the benefits of light spot homogenization technique, laser Schlieren system was qualified to reveal the flow structures with high resolution and sensitivity. Benefited from these features, the laser Schlieren can be applied widely in fluid mechanism studies, including high speed flows, jets, butterfly flow field and so on.
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High-speed real-time three-dimensional(3D) measurement is of great significance for the measurement of high-speed dynamic process. However, the projector needs a long time integration to project different gray levels, and needs a complicated gamma correction process, which greatly limits its measurement speed and accuracy. The appearance of defocus fringe projection technology provides a new perspective for high-speed dynamic 3D measurement. With the research on the feasibility of the combination of deep learning and traditional digital fringe projection 3D measurement technology, the development of fringe projection technology is also breeds new breakthroughs. In this paper, we combine the defocus fringe projection technology with deep learning, and propose a 3D shape measurement based on projector defocusing and deep learning. Experiments show that by collecting sufficient and comprehensive training data and after many reasonable trainings, this method can effectively eliminate the ripple error in the traditional three-step phase shift method and the measurement accuracy is comparable to that of the twelve-step phase-shifting method.
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In this paper, we simulated and analyzed the effects of guard-ring’s depth and space on the performance of silicon avalanche photodetector (APD) based on the traditional n+-p-π-p+ structure. Two shallow trenches (ST) outside of the active region was used as the guard rings and the effects of depth and the spacing between the two ST on the performance of silicon APD arrays was simulated and analyzed. In order to optimize the parameters of the shallow trenches, we calculated the different characteristics of APD under different conditions, including the characteristics of APD such as breakdown voltage, multiplication factor, dark current, photocurrent and so on. The result shows the breakdown voltage and multiplication of APD become higher because of the shallow trench guard-rings and they are related to the PN junction depth.
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Reflectance Transformation Imaging (RTI) is a computational photography technology that can enhance the legibility and the fine details of the sample. Colorless trace is a special kind of trace with shallow depth and its grayscale is similar to the background. It is difficult to perceive details of these traces by traditional observation and detection methods. In this paper, we propose some improved detection methods which combine RTI with the Canny algorithm to get more details of colorless trace. The threshold is one of the key factors which affect the performance of the Canny algorithm so we put forward a threshold selection method based on the gradient histogram of the image. Three detection methods that combine RTI with the improved Canny algorithm are proposed in this paper. The experimental results show that these detection methods can extract weak and colorless traces effectively, and would have great potential application in criminal investigation.
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The analysis of Hela cells are very dependent on the segmentation of cell images, but the difficulty of cell image segmentation comes from two aspects: cell itself and imaging technology. we present a method for automatic segmentation of Hela cell imaging in digital holography(DH) in this paper. By using a DH imaging system and a cell segmentation algorithm based on adaptive threshold segmentation and watershed algorithm, cells that adhere to each other or have irregular shapes in the image can be segmented.
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Life sciences are devoted to the research of all aspects of living organisms. As the basic unit of a living organism, biological cells are diverse and different. These differences are a direct reflection of their corresponding biological characteristics, so "seeing the cell more clearly" has been the goal of scientists at home and abroad. Based on the principle of coherent imaging, digital holographic quantitative phase microscopy imaging technology adopts digital recording and numerical reconstruction to realize phase retrieval and three-dimensional reconstruction. It has become one of the most promising methods in cellular research with better imaging efficiency, reconstruction accuracy, and stability. However, in the band-pass filtering process, tilt aberrations are often introduced due to manual frame selection of the +1 order spectrum, which is detrimental to the imaging quality of the system. To address this problem, this paper proposes a method to automatically determine the spectral center based on the surface fitting of a two-dimensional Hann window function, which improves the phase retrieval accuracy and imaging quality without reducing the computational speed. A more accurate spectral center can be obtained by conducting the sub-pixel spectral center of surface fitting. In addition, the accuracy is sub-pixel level and requires sub-pixel displacement correction of the tilted phase plane to obtain better quantitative phase retrieval results and imaging quality.
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High-speed three-dimensional (3D) shape measurement has become a very important technology in industrial manufacturing, motion detection and other scientific research. Although there are some methods to measure 3D surface patterns, it is still difficult to accurately measure the rapidly changing 3D high-speed scenes. Multi-frequency phase unwrapping usually uses a combination of noisy fringe images with different fringe frequencies for phase unwrapping, which has high accuracy and reliability. Benefiting from the success of deep learning in the field of computer vision in recent years, we combine multi-frequency phase-shifting and phase unwrapping with deep learning, and propose the high-speed 3D shape measurement from noisy fringe images using deep learning. Compared with traditional methods, this method can achieve more convenient and robust phase retrieval at high speed. Based on a good training model, the deep learning neural network can directly achieve the corresponding high-quality phase results after extensive learning of the data set collected at high speed. The experimental results demonstrate that this method can achieve 3D shape of the measured object with an accuracy of about 51μm at the camera frame rate of 700 frames per second.
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In order to better extract the infrared target information of images in dark scenes and retain more background texture details, an infrared and visible light image fusion algorithm based on fuzzy C-means clustering (FCM) and guided filter is proposed. Firstly, the target information is extracted from the source infrared image by FCM, and the target area and background area of the infrared image are obtained. Then, the target region coefficients and background region coefficients are decomposed into their respective high-frequency and low-frequency subband coefficients by using non-subsampled shearlet transform (NSST). Then, according to the different characteristics of different regions, different fusion strategies are adopted. In order to retain more target information, low-frequency subband coefficients of infrared image target area are selected as fusion coefficients of low-frequency target area, and high-frequency subband coefficients of infrared image target area are selected as fusion coefficients of high-frequency target area. In order to keep more texture details, the method of maximizing low-frequency subband image coefficients and information entropy is adopted in the fusion of low-frequency background region. The method of guided filter combined with dual-channel spiking cortical model (DCSCM) is used in the fusion of low-frequency background region. Finally, the final fusion image is obtained by NSST inverse transform. Simulation results show that compared with the existing algorithms, the fusion image obtained by this algorithm has prominent infrared target in subjective vision, clear background texture details and high hierarchy. In objective evaluation, the indexes are better than other algorithms as a whole.
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A portable and sensitive laser-induced fluorescence device combined with specific probes is developed for detecting the concentration of metal ions in solution. A 405nm laser diode is applied as an excitation light source to excite the fluorescence of the experimental materials, which is coupled into an optical fiber through a collimating and focusing lens group and then introduced into the spectrometer. Sterile water, alcohol and blue fluorescent microspheres are used to evaluate the detection capability of the device. We compared the fluorescence spectrum of probe solution mixed zinc ions with different concentrations from our device and a commercial fluorescence spectrophotometer. The detection sensitivity of our device is the same as the commercial spectrophotometer, and because of its small size, it can be used for on-site heavy metal detection.
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The all-optical fiber-based intelligent sensing system is one key technology for acoustic/ultrasonic structural health monitoring. Damages such as cracking or impact loading in civil, aerospace, and mechanical structures can generate transient ultrasonic waves, which can reveal the structural health condition. Hence, there is a great need to develop a high precision adaptive sensor for large-value strain signals with large frequency range that can extent to several hundred kilohertz in ultrasonic/acoustic sensing. In this work, we explore an intelligent system based on a fiber Bragg grating (FBG) and an erbium-doped fiber amplifier (EDFA), composing as a fiber cavity that offers significant advantages and higher performance in ultrasonic/acoustic sensing applications. The ASE light emitted from the EDFA and reflected by a FBG is amplified in the fiber cavity and coupled out by a 90:10 coupler, which is demodulated by an unbalanced Mach-Zehnder interferometer (MZI) composed by a 2×2 coupler and a 3×3 coupler. As the reflective spectrum of the FBG sensor changes due to excited acoustic waves, the shift of the laser output wavelength is subsequently converted into a corresponding phase change. We theoretically and experimentally calculate the three output signals using a differential cross-multiplication (DCM) algorithm to directly demodulate the wavelength shift of the FBG sensor. The experimental results demonstrate that the proposed FBG acoustic sensing system has high sensitivity and can respond the ultrasonic waves into the hundreds of kilohertz frequency range, which shows a potential for acoustic emission detection in practical applications.
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Printed Circuit Boards (PCB) are widely used, in which the PCB chips are the control core of the whole PCB Board and the pins of the chip are very important in the soldering process. Aiming at this demand, a laser triangulation detection platform based on line structured light is designed. The system emits a laser beam through the semi-conductor laser, which is diffusely reflected by the pin of the target object and its solder, and is then imaged on CMOS to form a point cloud pattern through weighted total least square method. Then, the height of each pin, the distance between each pin and the height change of PCB plane are calculated by the depth map. Fit the straight line of the lead edge by the least square method, measure the distance from the straight line to the straight line to get the distance between the leads, and use the change of the distance to judge whether the lead is misaligned.
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A Finite Element Method (FEM) to establish the model of CAT resistive anode and Square resistive anode is proposed. The characteristics of electrode charge signal are analyzed. The factors that affect the position reconstruction linearity of resistive anode are analyzed, including the geometric parameters and sheet resistance of the surface resistive layer, by calculating the amount of electrode charge from a simulated photon hit. It has been concluded that signal development time should be greater than 8R'C' ( R'C' =RC / μ2 ) seconds in order to ensure the root mean square (RMS) nonlinearity (%) of position reconstruction is less than 3% for these two resistive anodes, with capacitance C , and sheet resistance R of sensitive region.
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The development of photoelectric detection technology has promoted the development of the smart wearable market. Wristband heart rate monitoring equipment has become a familiar product to the public. However, according to related research tests, there is a large error between the heart rate monitoring data of the wristband device and the real data during exercise. This article proposes a dual-spectrum headband health monitoring system solution with ultra-small size, ultra-low power consumption, and high integration for the above problems, which converts the monitoring part from the common wrist to the forehead. The integrated monitoring system is as small as 11.8mm*5mm. Ultra-low power consumption design effectively improves the battery life of smart wearable devices. The dual-spectrum monitoring system adopts the reflected photoelectric pulse wave detection method, and integrates red light and infrared light to form a dual LED. The heart rate value is calculated through the collected photoplethysmography (PPG) signal. In the software algorithm processing, the Mallat algorithm of wavelet transform is first used for software filtering, and then the pulse wave signal characteristic points are identified. By comparing the system designed in this paper with the fluke blood oxygen simulator, the results show that the heart rate measurement error of the system reaches plus or minus 1% + 1 beat/min. In addition, the dual-spectrum health monitoring system can also use "cloud" big data analysis technology to provide more health information. It can also be used for the management of chronic cardiovascular diseases.
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Optical passive ranging is based on the light signal radiated by the object itself. The application of wave front coding technology to passive ranging systems simplifies the system structure and improves the ranging accuracy to a large extent. In this paper, the orthogonal coding passive ranging system with the cosine form of the mask function is investigated, and the optical transfer function and the light intensity distribution at the distances of 1m-4m and 1km-5km are simulated by numerical simulation to verify the rationality of the orthogonal coding ranging system, and the measurement error is about. ±0.1m.
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To unwrap the wrapping phase from phase measuring profilometry in 3D surface measurement, many spatial and temporal phase retrieval methods have been presented. However, spatial phase retrieval method often leads to errors because of discontinuous morphology, noise and fringe undersampling. Temporal phase retrieval method can solve this problem. But the method needs multiple frames of fringe images which would take much time. We proposed a novel absolute phase measurement method with few-patterns to overcome this problem. The proposed method combines an object reflectivity correction and a half-period gray-coded phase unwrapping algorithm. One group of precoded three-step phase-shifting fringe patterns are used to determine the wrapped phase, divide the region, and correct the surface reflectivity of the tested object, a frame of half-period gray-coded pattern is used to determine the fringe order. The proposed method can obtain a large number of codewords for fringe order without decreasing the intensity level for each stair. The result shows that our half-period gray-level coding (HGC) method is robust and efficient.
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Fused silica optical elements are widely used in large high-power laser devices, and the subsurface defects of optical elements directly affect the laser damage threshold and imaging quality. These defects are distributed within a few to tens of microns from the surface and cannot be detected by conventional imaging methods. The characteristics of small size, low density and wide distribution range make it difficult to detect nondestructively, effectively and quickly with conventional methods. In order to solve the above problems, an experimental system was built based on the principles of photoluminescence and dark field scattering. Use the different characteristics of fluorescence image and scattering image to carry out the research of subsurface defect detection. First, preprocess the original image. Second, calculate the offset of adjacent images, perform background homogenization processing on the image, and stitch the sub-aperture images, and then segment the full-aperture image. Then, a more effective subsurface defect extraction algorithm is proposed. Finally, etch the sample with HF and observe it under a microscope. Experimental results show that this method can detect weak defects on the surface and sub-surface at the same time, and can effectively separate individual sub-surface defects. This method has the advantages of lossless, fast and high precision. Moreover, based on a large amount of data, analysis and summary of the causes of defects, distribution characteristics, etc.. This method can provide certain guidance for the evaluation of laser damage threshold and processing technology of optical components in high-power laser devices.
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Fingerprints, a kind of reliable and accessible biological characteristic for individual identification, are commonly used on many occasions such as the mobile phone unlocking and criminal investigation. In this paper, a method based on fuzzy enhancement is proposed to segment fluorescence images of invisible fingerprints which are induced by ultraviolet laser on porous paper substrates. With the purpose of achieving the segmentation of latent fingerprints, the fuzzy enhancement and morphological operators are employed to extract the minutia while the ridge structures and valley structures are ruined by intensive background noises. In combination with the directional image, the method proposed could effectively remove the noises and obtain clear visible minutia simultaneously. The effectiveness of the method proposed shows great promise for further analysis of latent fingerprints and even in criminal investigation.
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Starting from the collimated beam to be solved by the lighting system, based on the Gaussian optical theory, the transformation of Gaussian beam through the lens is deduced, the principle of large magnification collimating and expanding beam system is analyzed, and the design of collimating and expanding beam system changing the laser beam diameter and divergence angle is realized. It is verified by simulation, which meets the requirements of the lighting system for parallel light incidence
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With the increasing demand of navigation and positioning services, the accuracy and safety of traditional navigation system have been limiting factor of future application. The development of quantum technology brings hope to the research and development of a new generation of navigation system. In this paper, the application of quantum technologies in fiber optic gyroscope is introduced and analyzed.
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Deformation monitoring is an important content of dam safety monitoring. This article firstly introduces the origin and development process of dam safety monitoring. Dam deformation monitoring is then reviewed. Artificial dam deformation monitoring technologies including tension line method, alignment method, forward intersection method, traverse method, positive and negative vertical line method, geometric leveling method and hydrostatic leveling method, as well as automatic dam deformation monitoring technologies including measuring robot, photogrammetric technology, global positioning system (GPS), three-dimensional laser scanning technology and fiber optic sensing technology are discussed by comparing their principles, advantages and disadvantages. Main problems of current dam deformation monitoring procedure are summarized. Based on that, the development trends in dam deformation monitoring are finally predicted.
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In this paper, we introduce an optimal peak search strategy of Brillouin gain spectrum (BGS) and denoising method of central wavelength of BGS based on Brillouin optical time domain analysis (BOTDA) system. The system utilizes both up shifted and down shifted continuous-wave light to generate Brillouin scattering light, while using the amplified pulsed light to boost the signal by stimulated Brillouin scatting effect. In order to obtain an accurate strain change of fiber under test (FUT), the peak of each Brillouin scattering spectrum must be accurate and precise. In addition, the intensity of shifted light should be stable as well. Therefore, we propose a novel peak search algorithm of BGS of a BOTDA system, which keeps the right central wavelength even if the scan step of the frequency is in large condition. Besides that, we also proposed a time domain denoising method to enhance the signal to noise ratio. We also implement static experiments to verify our proposed scheme. Strain/temperature tests were taken out evaluate the performance of the BOTDA. Results showed that the resolution of BOTDA system could reach 13με/0.65°C at 1 km fiber cable.
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As a new generation of optical surfaces, free-form surfaces have a non-rotating symmetric structure and complex characterization ability. With the rapid development of optical manufacturing technology and detection technology, it is gradually applied in optical design. But the free surface structure is complex, different optical faces have different surface type features, no good generality. Combining the characteristics of free-form surfaces, proposed the conversion algorithm between different faces and deduced the common surface conversion, presented the use scene and the optical system optimization method, and verified the optical system design examples, proposing new ideas for optical system design. The design results show that the design optimization using the surface conversion algorithm helps to improve the image mass and skip the local minima.
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Image demosaicing and denoising are two important processes in the ISP pipeline of mobile cameras, because almost all mobile cameras in use today require colorful images generated by demosaicing algorithm, and the small sensor area of mobile cameras triggers low signal-to-noise ratio. Over the years, a considerable number of sequential demosaicing and denoising methods have been proposed, while they suffer from estimating the noise distribution and adjusting the hyper-parameters in order to balance demosaicing and denoising. There exit simultaneous demosaicing and denoising methods solving these problems. But they lack guidelines designed for mobile cameras. We propose a Plug-and-Play (PnP) demosaicing and denoising method on mobile cameras. Our method is built on PnP demosaicing framework which is derived from variable splitting theory. Any color demosaicing algorithm (i.e., bilinear, Malvar) can be plugged into our framework. We novelly trained an ISO conditioned denoiser for the framework and iteratively apply the denoiser in it. The ISO conditioned denoiser not only removes noise from the demosaicing procedure itself but also noise from camera sensors. By introducing ISO settings to the denoiser, our method takes possession of the adaptability and robustness in various capturing environments under different camera settings. Our method has only two hyperparameters to tune, which eases the hyper-parameter adjustment in sequential demosaicing and denoising methods. Extensive experiments on synthetic datasets show that our method performs better than sequential demosaicing and denoising methods and is practical for mobile cameras.
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A new method for defect recognition of foam sandwich structure composites based on morphological filtering is proposed in this paper. Firstly, the terahertz frequency modulated radar imaging system is used to detect the foam sandwich structure composites to obtain the original detection signal, and the original detection image is obtained by using amplitude imaging method. Secondly, the original detection images are transformed to binary images by setting threshold values. Thirdly, based on the morphological filtering theory we carry out closing operation to fill the inner tiny holes in the binary images, and connect the discontinuous adjacent targets. Finally, the opening operation is used to remove the redundant small objects in the image, and obtain the final detection result image. In this paper, the imaging detection of polymethacrylimide foam sandwich structure composites is carried out, and the original detection signal is processed by using the above method, the resulting images with the prefabricated defect effectively recognized is obtained.The accuracy of the proposed method for defect recognition is evaluated by calculating and comparing the error ratio of the defect area in the processed image and the original detection image relative to the actual defect area.The results show that the proposed method can effectively recognized the prefabricated defects in foam sandwich structure composites and optimize the size of the defects to be close to the actual defects, which is conducive to the further application of terahertz nondestructive testing technology in foam sandwich structure composites.
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With the change of working time and environmental conditions, the performance of optical fiber coil has deteriorated, which seriously affects its long-term stability. In recent years, the performance of fiber optic gyroscope(FOG) has been continuously improved, and the requirements for adhesive of fiber optical coil have become higher and higher. It is required not only to meet the stability of coil potting, but also to resist high and low temperature environment for a long time during operation of FOG. In view of this, the study in the environmental stress effects of optical fiber coil adhesive was carried out. Based on optical fiber coil, this paper introduces the environmental stress and its influence mechanism of polymer materials aging, and focuses on the optical fiber coil adhesive aging behavior, as well as analyses the physical and chemical properties of adhesive. On basis of this, environmental stress tests were carried out, and the physical and chemical properties of adhesive were obtained. The experiment and analysis results showed that the glass transition temperature will significant transfer under excessive ultraviolet exposure or a long time high temperature of 85degree Celsius and low temperature of -45degree Celsius, and the adhesive viscosity significantly increased in high humidity environment. Under the comprehensive effect of various environmental stress, the adhesive properties will changed and further affect the stability of optical fiber coil.
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Accurate measurement of the surface temperature of the hot-end components of aero-engines is of great importance for health monitoring and design of the engine. As a non-contact temperature measurement technology, the phosphorescence temperature sensing technology based on thermal quenching effect developed rapidly in recent years. It obtains real-time temperature information by measuring the decay time or intensity ratio of the phosphor on the surface of the high-temperature component. Aiming at the problem of the high temperature failure and shedding of the phosphorescent film, polymer derived ceramics (PDC) is used as the adhesion layer, whose thermal and mechanical properties can be easily controlled by doping, to improve the high-temperature oxidation resistance and adhesion of the phosphorescent film. The phosphor temperature sensing film with Y2O3:Eu3+ phosphor and perhydropolysilazane (PHPS) precursor ceramics as temperature sensing substances and high-temperature bonding layer respectively is made on alumina and nickel-based alloy substrates. The phosphorescence emission spectrum and 611nm/620nm phosphor intensity ratio were measured with the 407nm excitation laser. The results show that the phosphor film on the aluminum oxide insulating substrate has higher phosphorescence intensity and temperature sensitivity than phosphor film on the nickel-based alloy metal substrate, the phosphorescence intensity decreases with the increase of sintering temperature, and the phosphor film using PDC as the bonding layer has the characteristics of high temperature oxidation resistance and strong adhesion.
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In this paper, the demand for value transfer and traceability in the quantitative measurement of infrared radiation characteristics in the field environment is analyzed, and the necessity and significance of value transfer and traceability are expounded. According to the requirements of infrared radiation quantity transfer and traceability in the field environment, the development of infrared radiation quantity transfer radiometer is completed, which mainly includes athermalized optical system, diaphragm module, chopper, reference blackbody module, infrared detection module, signal acquisition system and so on. It is applied in the field environment. By comparing the measurement method with the standard blackbody radiation source, the quantity transfer of a certain type of field target characteristic measurement equipment is carried out, and the relevant data are analyzed. The analysis results show that the measurement uncertainty is better than 1 % by traceability in the field environment. Therefore, the measurement uncertainty of the infrared radiation characteristics in the field can be effectively improved by transmitting the infrared radiometer through this value and cooperating with the standard blackbody radiation source, and the traceability chain of the infrared radiation value in the field environment can be improved, which has good application value.
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With the rapid development of the fiber optical gyroscope technology and its widely applies, the multi-axis Fiber Optical Gyroscope (FOG) such as the triaxial FOG and its system are popular more and more.[1-2] For the requirement of less weight and less size,[2] the multi-axis FOG needs higher electromagnetic structure design skills and more critical devices compared with uniaxial FOG. The Z axis of some triaxial FOGs occur the problem of the bias instability over tolerance, which is a real engineering case in our development process. In this paper experiments are carried out after the influence factors are analyzed. Results show that the modulation of the Z axis is interfered by the other two axes. There are three test steps in the experiment including the optical unit test, the modulator test and the modulator shield test with different materials. A simulation of the original shield structure is applied in order to find the structure defects. Two defects are found on the base of the analysis of the electromagnetic structure check. The main defect is that there is a hollow structure on the top of the Z axis in the system which causes extra electromagnetic circuit from the other two axes. The other defect is that each axis is exposed under complex circumstance with less modulator shield. The modulator with less shield has the merit of less thermal stress owing to the free contraction between the metal packaging and the modulator. In our triaxial FOG system, the modulator shield structure inherits from the uniaxial FOG with less shield, in order to decrease the thermal stress. As we know, in the uniaxal FOG the modulator will still robustly work under a clean electromagnetic circumstance, even there is no shield upon the modulator. However, in the multi-axis FOG there are obvious crosstalk interference between the different axes, when all axes are working together with a close frequency. Based on the experiments and the analysis, the following design principles are given. Firstly, the thermal factors, the vibration factors and the electromagnetic factors should be considered at the same time when the modulator shield is designed. Secondly, the Fe-Ni material has better shield effect than the common metal like Aluminum. Thirdly, there are two kinds of resins, the hard buffer and soft buffer, to connect the Y-junction fiber tail and the metal capsulation. This paper is of great use to the engineering of the multi-axis fiber optical gyroscopes and the fiber optical gyroscope system applications.
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The object tracking accuracy may be decreased because of the camera jitter, making it extremely hard for object tracking and trajectory analyzation. To achieve accurate video stabilization, the movement of camera can be analyzed and predicted based on the previous camera jitter sequence. In the area of sequence prediction, the long-short term memory (LSTM) network shows the potential in sequence forecasting, here we use LSTM network in camera jitter prediction and video stabilization. In this paper, we propose a video stabilization algorithm based on multi-region grey projection method and LSTM encoder-decoder network. Our algorithm calculates the motion of the camera through the gray projection of four areas in each frame, then filters out the main movement direction and jitter of the camera. The LSTM encoder-decoder network receives the camera jitter sequence, predicts the camera jitter then stabilizes the video. We to verify the performance of the proposed video stabilization method. We tested the proposed video stabilization algorithm on the jitter videos, which is made by the VisDrone dataset video modified with our recorded camera jitter. Experimental results demonstrate that the proposed method can achieve the video stabilization in real time, and increase the accuracy of object tracking and trajectory analyzation.
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Intelligent camera for distributed reconfigurable remote sensing satellite system should be lighter to be installed on small or micro satellite. In this paper structure design of intelligent camera for distributed reconfigurable remote sensing satellite system was presented in detail. Three mirrors anastigmatic (TMA) optical system was used in the intelligent camera. Structure of the intelligent camera consists of the primary mirror module, the secondary mirror module, the tertiary mirror module, the focal plane adjusting module and the main framework module. Structure of the intelligent camera was designed so that mounting points of the camera were distributed more dispersedly and the camera's center of gravity was closer to the satellite platform. In this way better dynamitic characteristic was realized. Aluminum alloy framework was used to realize better thermal characteristic and lower weight. In order to compensate variation caused by vibration of spacecraft launch and change of temperatures on orbit, precision of focal plane adjusting module is no more than 10μm and the range of focal plane adjusting is ±2.5mm. Results of experiments indicate that total weight of the intelligent camera for distributed reconfigurable remote sensing satellite system is about 8kg and can satisfy the demand of the mission.
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As a high-precision angular rate sensor, high-precision fiber optic gyroscope (HP-FOG) can be used for space positioning, strategic missile guidance and submarine navigation. With the further improvement of the demand for navigation accuracy under deep and open sea conditions and satellite rejection conditions, the goal is to manufacture FOG with higher accuracy and sensitivity. The noise of FOG has become the key to restrict its application in high-precision field. In this paper, the noise source of FOG is analyzed, and the method of using semiconductor optical amplifier to suppress relative intensity noise and feedback adjustment to reduce noise is given. In theory, we propose a scheme of FOG using three photon states as light source to improve the detection sensitivity. In theory, this scheme can realize three times super-resolution measurement.
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The optical wave wavefront measurement system can perform non-contact real-time quantitative monitoring of the gas flow rate according to the gas density changes in the wind tunnel test. Since the quality of the optical surface of the wind tunnel window directly affects the acquisition accuracy of wavefront information, it is necessary to evaluate the adaptability of the opto-mechanical structure to fluid load in the development stage. To solve this problem, this paper proposes a gas flow field change model based on Finite Element Analysis (FEA). By calculating the fluid-structure coupling response of the wind tunnel window, the displacement field of the wind tunnel window and the maximum displacement of the node are obtained. It is 0.00018mm, and the result shows that the window glass has good environmental adaptability at a flow rate of 885m/s.
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An all-fiber Fabry-Perot interferometric sensor is demonstrated both theoretically and experimentally. The proposed structure is designed and fabricated by chemical etching combined with arc discharge welding and tapering. The single-mode fiber (SMF-28) with one end face flattened is inserted vertically into the hydrofluoric acid, then welded with another SMF-28 by arc discharge, to form a bubble by welding and tapering, which exhibits a three-beam interference phenomenon. High-temperature sensitivity of 12.88 pm/°C is obtained at the large temperature range from 50 to 300 °C, with excellent linearity of 0.9956. The Fabry-Perot Interferometer , with low processing cost and high performance, can provide a useful application in temperature sensing prospects.
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With the development of visual human-computer interaction, non-invasive eye-tracking technology has been applied in medical diagnosis, psychological research, augmented reality and other fields. As a key step of video-based eye tracking technology, pupil detection requires strong robustness, real-time performance and high precision. Although many pupil detection algorithms have been developed, pupil detection is still a challenge when there are so many interference factors such as bright light, reflection, eyelid or eyelash occlusion, or low image resolution. Aim to address the above difficult problems of pupil detection, this paper uses cascaded Haar features and Otsu dynamic threshold segmentation to improve the performance of the existing pupil detection algorithm. The performance of the improved algorithm is verified with the public human eye image dataset from Swirski with high off-axis and severe eyelash occlusion. The results show that the accuracy of the improved algorithm is 86.3% and 89.7% in the error range of 5 pixels and 10 pixels, respectively. The detection algorithm in this paper can provide accurate pupil center coordinates for eye tracking, which lays a foundation for the high-precision calibration and measurement of the following eye tracker.
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The bandwidth of the fiber optic gyroscope is an important indicator of its frequency characteristics. When the environmental conditions is under high dynamic such as vibration and sharp turns, the measurement accuracy of fiber optic gyroscope is greatly affected due to the limitation of the frequency characteristics of fiber optic gyroscopes. And the traditional bandwidth measurement method is to record the angular vibration’s amplitude and frequency of the turntable and the output of fiber optic gyroscope, and then use the least squares method to obtain the bandwidth of fiber optic gyroscope. However, the output frequency of the turntable’s circular grating encoder is not high enough, usually less than 100Hz, which cannot reflect the more comprehensive dynamic performance of the fiber optic gyroscope. And the manual operation test is always cumbersome. All of these limits the further research on the dynamic performance of fiber optic gyroscope. Therefore, this paper proposes a fiber optic gyroscope bandwidth evaluation method based on laser Doppler measurement technology. Then, an adaptive modal decomposition algorithm is proposed, which can adaptively decompose complex nonlinear and non-stationary signals into multiple frequency components. Our system can realize high-frequency, high-precision and non-contact, which is of great significance to the research of the dynamic performance of the fiber optic gyroscope.
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Fiber optic gyroscope (FOG) has the advantages of small size, light weight, large dynamic range, fast start up and long life. It can be widely used in military fields and civil fields. As the performance of the optoelectronic devices in the FOG varies with the temperature, the performance of the FOG will be affected. In the use of the carrier high speed, the scaling factor error caused by temperature change is the main error of the FOG, its effect on accuracy is much greater than random drift. FOG often needs to work in a wide temperature range, so the scaling factor needs to be modeled and compensated. Because of the temperature error of the scaling factor is very non-linear, the accuracy of using the traditional polynomial fitting method to compensate the scaling factor is poor. The neural network can approximate any continuous function with any desired accuracy, so this paper uses the BP neural network method to compensate the temperature error of the FOG scaling factor. First, this paper analyzes the error mechanism of the scaling factor, and establishes a theoretical model of the temperature error of the scaling factor. Then the FOG scaling factor in the full temperature range is measured, and the temperature error of the scaling factor is modeled and compensated by using the above two methods. It can be seen from the compensation results that the neural network model can get a good compensation effect, and the accuracy is better than the polynomial fitting method.
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Before the inertial instrument unit (IMU) is equipped on the carrier, its dynamic performance needs to be measured with a dynamic test equipment (DTE), such as vibration table, turntable and.so on. It is very difficult to separate the internal error of the DTE from the IMU navigation error. Traditional attitude measurement methods cannot simultaneously meet the measurement requirements of non-contact, high precision, large bandwidth, high speed and high sensitivity. Therefore, there is an urgent need for a third-party attitude performance measurement and evaluation system to realize the calibration of IMU dynamic performance and equipment error, which is of great significance for improving IMU dynamic performance and reducing test equipment error. Attitude measurement refers to the measurement of the rotation angle of a space object around three orthogonal axes. In order to achieve non-contact, high-precision, large-bandwidth, high-speed and high-sensitivity dynamic attitude measurement, this paper proposes a three-dimensional dynamic non-contact attitude detection demonstration based on Doppler laser vibrometer (DLV), expounds the principle of the vertical deflection of the pentaprism, establishes a mathematical model of the optical path deflection error of the pentaprism that affects the measurement accuracy, analyzes the key factors that affect the measurement accuracy and builds an experimental system to verify the measurement plan. When the measurement angle is not less than ±10°, the three-axis angle measurement accuracy is less than 0.01°.
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The Navigation and Terrain Camera of Tianwen-1 Mars Rover is mainly used for the guidance, navigation and control of the Mars rover, and it will also be used for scientific research works.Due to the complexity of the working environment of the Mars rover, its optical imaging system is easily affected by stray light, which forms stray light radiation on the image plane, thus reducing the imaging quality and affecting the accuracy of navigation. In this paper, the variation of irradiance of image plane with incident angle in camera field of view is studied, and the irradiance distribution of each lens surface is compared and analyzed. Combined with the principle of bidirectional reflectance distribution function (BRDF), the reason of irradiance variation law is analyzed. Referring to the results of the irradiance distribution analysis, it can avoid the influence of the stray light in the specific direction on the normal imaging of the camera in the actual detection process. The imaging quality and aberration of the optical system are analyzed and evaluated by combining the spot diagram, MTF curve and Seidel coefficient, and the results meet the needs of practical application. Then the imaging quality change of the optical system in the range of -110℃~60℃ are analyzed. Finally, the tolerance of the whole system is analyzed.
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Locating the pupil circle is an important step in iris recognition. As the light shines on the pupil, a bright reflection spot is formed in the iris image. In the process of iris location using Hough transform, location accuracy will be affected, because the reflection spot cannot be eliminated in practical optical system. Therefore, we proposed an algorithm to eliminate the reflected light spot in the pupil. The average gray value of the iris image can be obtained by using the gray histogram of the iris image. Then convolution of iris image with summation matrix of ten by ten is obtained, and the sum of gray values is less than a hundred times the average gray value and the approximate position of pupil can be found out. The pupil position is used to get the1 approximate position of the reflected highlight spot. The threshold is set to average threshold plus 128, and the point in the pupil field that is larger than the threshold can be obtained, and the position of the reflection point can be determined. The positions of the spot are set to zero. Using the algorithm, the number of highlight point in the binary iris image is reduced effectively. Thus Hough circle location would get higher location accuracy.
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The integration of quantum key distribution (QKD) devices with the existing optical fiber networks is of great significance in reducing the deployment costs and saving fiber resources. Wavelength division multiplexing (WDM) is expected to be a desirable approach to fulfill this ultimate task. In this paper, we analyze the dominant noises in WDM-based QKD system and optimize the key parameters based on a modified model with 200 GHz channel spacing. Then, an appropriate decoy-state method is adopted to estimate the system performance considering statistical fluctuations. Finally, a three-layer artificial neural network is used to train and predict the optimal mean photon numbers within different situations. Our work provides a useful method for the parameters optimization of WDM-QKD system and accelerates the practical development of QKD that coexists with the current backbone fiber infrastructure.
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Binocular stereo vision technology plays an essential role in the intelligent manufacturing system due to the advantages of high accuracy and non-contact. However, for the measurement of components with highly reflective surfaces such as metal and ceramic, the specular reflections affected by the complex light field lead to the failure of feature matching and the decrease of measurement accuracy. This paper proposes an imaging strategy for binocular vision and a high dynamic image processing method to suppress the effect of specular reflection for stereo matching. Firstly, the mechanism of highlight generation in the image is analyzed by combining the illumination reflection theory of the BRDF model. Then, a binocular vision system with a parallel optical axis is built to capture images under different illumination conditions. The image processing algorithm of high dynamic range image fusion is studied, and an algorithm based on tone mapping and weight fusion is implemented to remove the high-lights. Finally, an experiment was performed to verify the effectiveness of the proposed method by a robust and fast matching algorithm. An image evaluation method based on BRISQUE further demonstrates the effectiveness of the method. Compared to the original images, the quality score of the HDR images is lower, which means that the processed images are of better quality. Moreover, the method provides an increase of 23.33% in image matching accuracy, which verifies the availability applied in the measurement of highly reflective surface components.
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As one of the traditional Seidel aberrations, image field curve is a common problem in lens design. Moreover, because the Petzval field curve is affected by the distance between the positive and negative power, the lens must be made longer to achieve perfect field curve correcting, which is a difficult problem for almost every design. Benefit from the advanced optoelectronic chip technology, some companies produce curved surface sensors to solve the image field curve. Curved CMOS is to bend the sensitive area to better receive the light from the edge. As long as the lens design matches the curvature of the sensor, the edge image quality can be effectively improved, and the edge image quality problem can be solved. The curved surface CMOS can also make the edge light direct to the edge of the CMOS, so that the sensitivity of the edge can be greatly improved. In this paper, an Ultra High-Definition large aperture lens for full frame surface sensor is designed. The full frame surface sensor is introduced into the lens design to improve the edge image quality and solve the problem of edge light loss on the basis of large aperture. The focal length of the lens is 50 mm, and the F1.4, the field of view angle is 46 ° and the MTF (Modulation Transfer Function)of the whole field of view is <0.4.
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We proposed a design method of infrared video processor, hereinafter referred to as processor, used on geostationary orbit (GEO), for the performance of detector degraded after long time working in the complex space environment. Compared with the traditional design, this method used on-obit calibration technology to update the image preprocessing algorithm parameters and defective pixels. It improved single event effect (SEE) ability and implemented updatable function for the program of main controller, by used on-obit dynamic refresh and injection technology. The experimental results show that, the image quality kept stable when the performance of detector degraded. And the imaging system worked normally, and no need to reload the program of main controller when SEE occurs. It can also update and load the program of main controller with bus instruction. This method ensures the processor working normally in harsh space environment, and provides technical expertise for the follow-up design of processor.
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A multiplexed gas sensing network based on hollow-core photonic crystal fiber (HC-PCF) and active intra-cavity absorption spectrometry is designed and demonstrated experimentally. Sensing channels are extended to eight by using hybrid dense wavelength division multiplexing (DWDM) and time division multiplexing (TDM). What’s more, wavelength scanning technique combined with voltage gradient method are adopted in the designed sensing network, which improves the sensing efficiency at least five times when comparing with the whole scan. In experiment, by recording and analyzing the laser output intensity at acetylene absorption peaks of 1528.01 nm and 1530.37 nm, the minimum detection limit (MDL) of 30.16 ppmv and 26.28 ppmv are achieved, respectively. Therefore, the designed gas sensing network can realize detection of low-concentration gas with high capacity and efficiency.
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Hyperspectral Images (HSI) contains hundreds of spectral information, which provides detailed spectral information, has an inherent advantage in land cover classification. Due to the shortage of spatial resolution of spaceborne hyperspectral data, previous study mainly focused on studying the natural spectral signature of the target and distinguished different object categories through hand-crafted spectral rules or supervised learning-based models. With the increase of spatial resolution of hyperspectral data, the study of joint characteristics extraction of the spectrum and spatial information is of great significance. Benefit from the remarkable learning ability of convolutional neural networks (CNN), deep learning methods can better realize the extraction and fusion of spatial and spectral features. In this paper, a new airborne HSI from Liaozhong area of Shenyang with the sub-meter resolution is introduced. Different data combinations and CNN-based methods are employed in the experiment to illustrate which factors are effective in improving the accuracy of hyperspectral classification. The experimental results show that the double-branch structure is more coducive to improving the classification accuracy, and the principal component analysis (PCA) methods is more effective than hand-crafted band selection in dimension reducing while maintaining accuracy.
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Polarimetric imaging is a technology which collects the polarimetric information of targets and forms an image. It has been proven that polarimetric imaging method has unique advantages at the area of target detection in the haze, dust and other scattering medium background. In this paper, a new polarimetric dehazing method is proposed based on low-pass filtering techniques. A linear polarization camera is employed to grab images with four different polarization directions, and the low-pass filtering operation is applied to remove the high-frequency components which contain the information of noise and targets, which will improve the accuracy of estimation of airlight, and then the haze background and objects in these images can be separated based on the difference of their polarization characteristics. For the purpose of verifying the effectiveness of the proposed method, multiple groups of images of advertising boards and buildings have been grabbed and processed by this method, and the experimental results indicate that the presented scheme can reduce the adverse influence of haze and improve the visual range effectively.
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To analyze the interference effects on a certain shortwave radio of low frequency wide pulse electric field, irradiation experiments are carried out. Through theoretical analysis, simulation and experiment, the effect rules and interference mechanism are confirmed. The results show that low frequency wide pulse electric field, which rise time is not less than 10ns and the pulse width is more than 1ms, can interferes the normal working performance of shortwave radio. But it cannot damage the shortwave radio even the field intensity reaches 100kV/m. The main interference phenomenon is communication interruption, while it can comeback in a few seconds, usually about three or five seconds. It should be noted that the interference phenomenon happens in a certain frequency range. And in the range, the threshold interference field intensity rising with the increase of the frequency.
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Power Integrity (PI) issues with the development of high-speed digital circuits, simulation is the best way to solve it. In this paper, the HyperLynx simulation software is used in the PCB design process, in order to optimize the schematic diagram design and guide the PCB layout and wiring. The method of verifying the correctness of PCB design in the simulation after wiring is also introduced. In the process of simulation, combined with the relevant theory of PI, according to the simulation results, the method of optimizing circuit design is proposed, and the simulation waveform is verified. The results show that PI simulation in PCB design is of great significance to improve PCB design quality.
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The paper proposes a high-resolution static strain sensor based on the random fiber laser (RDFL) and the beat frequency method. A π-FBG is used as the sensing element in the RDFL. A narrow-linewidth laser source is frequency-locked to a reference π-FBG by the Pound-Drever-Hall (PDH) technique. The RDFL beats frequency with the frequency-locked laser to achieve a narrower-linewidth beat frequency signal. The 3 dB linewidth and the frequency shift of the beat requency signal are respectively 380 Hz and 27.2 kHz. By tracing the frequency shift of the beat frequency signal, a static strain resolution of 0.18 nε level is achieved.
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A single photon array imaging lidar(SPAIL) based on the Geiger model has the characteristics of small size, high-sensitivity detection, high-resolution, non-scanning imaging and can realize the characteristics of undistorted three dimensional image of dynamic/static targets. However, In the case of high resolution, the instantaneous imaging field of view is small. To achieve high-precision recognition and tracking of targets in a large dynamic range, a high-precision servo and tracking system is required to completes the closed-loop tracking control of the target. A SPAIL platform incorporating a 64×64 array of Geiger-mode APD is constructed for validation and demonstration. The SPAIL is composed of three modules: scanning unit, optical transmitting and receiving unit, detection and processing unit. The scanning system uses a 26-bit high-precision encoder as the position loop detection element. The transmitting laser has a working wavelength of 1064.1nm, a working frequency of 10khz, a pulse width of 2ns.Subsequently, The optical receiving aperture of the laser is 60mm, and the line width of the narrowband filter is 0.1nm that filter out background noise interference. Multi-frame image correlation and dynamic threshold adjustment are used to complete target recognition, and the target tracking algorithm of Mean shift is used to extract the target. Under good weather conditions, during the dynamic scanning process of lidar, the target distinguished the 6km tower is completed respectively. SPAIL completed the real-time tracking and measurement of the 300m flying UAV (Unmanned Air Vehicle). In the future, the fusion of laser array image and visible light/infrared image information will be researched.
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Compressed sensing theory is a new sampling theory, which provides a method to recover the original signal from a small number of samples. For sparse signal and compressible signal, compressed sensing theory compresses the signal while sampling. It combines the sampling process and compression process. It breaks through the traditional Nyquist sampling law and saves a lot of storage, transmission, computing and other resources. This theory not only reduces the cost of storage and transmission of digital image and video acquisition, but also provides a new opportunity for the follow-up research of image processing and recognition, and promotes the combination of theory and engineering application. It includes three parts: sparse representation of target, design of measurement matrix and reconstruction of target. Reconstruction algorithm is a key step in the process of compression imaging, which determines the accuracy and speed of image reconstruction to a certain extent, so it is very important to select the appropriate image quality evaluation index. The image quality evaluation of existing reconstruction algorithms mainly focuses on peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The advantages of these two algorithms lie in simple algorithm, fast inspection speed, which are suitable for evaluating the advantages and disadvantages of algorithms, but the disadvantage is that they can only be evaluated on the basis of known original images. In the actual imaging process of compressed sensing, it is impossible to obtain the original image, so we need to use an image quality evaluation method which is not based on the original image.
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For the current ground-based space target surveillance system in China, the task response time is long, the target monitoring system is time-sensitive, and the space-based on-orbit monitoring current monitoring system usually has a small field of view, and the field of view is generally 6°, the monitoring range is limited, and the tracking arc is limited. This paper proposes a design of space-based large field of view monitoring camera. The selection and experimental analysis of high quantum efficiency and low noise detectors, detector refrigeration design and thermal test verification, big angle and high suppression ratio stray light design, this key points of high sensitivity detection camera for dim target are discussed in this paper, and lay the foundation for quickly acquiring the position and orbit information capability of long-range dim targets, providing high-precision cataloging of fast-moving dark space targets, improving the monitoring performance and real-time performance of surveillance systems in China.
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As a non-contact three-dimensional measurement method, line structured light measurement is widely used in three-dimensional shape measurement due to its fast speed, high accuracy, and convenient implementation. The line structured light extraction is one of the most important step in the line structured light measurement system. Most traditional algorithms are based on the Hessian matrix or the light intensity distribution of the light strip section to extract the center. In this paper, a novel algorithm based on ridge tracking is proposed to extract the center of the light strip, the approximate direction has been used to estimate the direction of the light strip. Experiments have proved that this algorithm can be applied to the extraction of light strips in a variety of scenes, and has good accuracy and noise resistance.
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Shortwave laser is more and more widely used in gated imaging, tracking and pointing, communication and other fields. For the requirement of 1550nm high power laser source, The paper analyzes the realization way, and realized the 1550nm high power laser lighting source. We use multichannel semiconductor laser coupling to realize the high-power light source, and uses fiber coupling to realize the uniform spot. On this basis, an extended collimator is designed, which achieves 10 times of high-power The beam divergence angle can reach 9 mrad to 90 mrad, and the RMS value can be less than 1/4 of the wavelength at each magnification of the wave phase difference, which can meet the needs of engineering application.
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With the rapid development of nucleic acid molecule detection technology, nucleic acid detection devices have become a global research hotspot in recent years. This paper uses multidisciplinary fusion technology to propose a nucleic acid fluorescence detection design scheme. The device is mainly composed of a motion module and an optical system. Among them, the motion module uses an S-type variable acceleration control method to precisely control the movement of the motor. The stable and accurate operation lays the foundation for the collection of fluorescent signals; the optical system uses LED as the fluorescent excitation light source. The LED collimated uniform light path is designed. Use image stitching to stitch the collected images into a complete image for analysis. Finally, measure the operating error of the motor, the average error does not exceed 14um; simulate the fluorescence signal acquisition system and collect the image of the fluorescent film, the image fluorescence is uniform, which verifies the rationality of the fluorescence acquisition system; collects simulated samples and blank control images , Analyze the stitched images, and the results clearly distinguish the simulated samples and the control group.
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The composition of multiple-layer Light Detection And Ranging (LiDAR) and camera is commonly used in autonomous perception systems. Complementary information of these sensors is instrumental in the reliable surrounding perception. However, it is a difficult work for obtaining the extrinsic parameters between LiDAR and camera, which must be known for some perception algorithms. In this study, we present a method, using only three 3D-2D correspondences to compute the extrinsic parameters between Velodyne-VLP16 LiDAR and monocular camera. The procedure is that 3D and 2D features are extracted respectively from the point cloud and image of a custom calibration target and then the extrinsic parameters are obtained based on these features by the perspective-3-point (P3P) algorithm. Outliers with minimum energy at geometrical discontinuities of target are used as control points for extracting key features in LiDAR point cloud. Moreover, a novel method is presented to distinguish the correct solution from multiple P3P solutions. The method depends on conic shape discrepancies in spaces of the different solutions.
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