Range-gated active imaging is a prominent technique for night vision, remote sensing or vision through obstacles (fog, smoke, camouflage netting…). Indeed, by means of the "range gating" or the "time gating" technique, it is possible to eliminate the backscattering effects during the propagation of the illuminating light through scattering environments such as rain, snow, fog, mist, haze or smoke. The elimination of the backscattering effects leads to a significant increase in the vision range in harsh environments. Surprisingly, even if a lot of authors estimate that range-gated imaging brings a gain when used in scattering environments, there are no studies which systematically investigate and quantify the real gain provided in comparison with classical imaging systems in different controlled obscurant densities.
We put in evidence that the penetration depth improvement can drastically vary with the type of obscurant and with the illumination wavelength. For example, it can be improved by more than a factor of 10 for specific smokes to only a factor of 1.5 for water droplet based fog. In this paper, we thoroughly examined the performance enhancement of laser range gating in comparison with a color camera representing the human vision. On the one hand, we studied the influence of the different types of obscurants and showed that they lead to very different results. On the other hand, we examined the influence of the illumination wavelength.
As the global attenuation of an obscurant is the sum of its absorption and its diffusion, we also report on some experimental results in which we tried to separate the influence of each of these two parameters. To demonstrate the influence of the absorption by maintaining the diffusion constant, we worked with the same type of smoke, but with different colors. To work with different levels of diffusion, we maintained the particle material constant and worked with different particle diameters.
KEYWORDS: Sensors, Signal detection, Detection and tracking algorithms, Photon counting, Interference (communication), Aerosols, Signal to noise ratio, Signal processing, Databases, Atmospheric modeling
Photon counting technologies are developed and could be used in the future to measure the return from laser induced fluorescence. Currently, the spectral detection of light emitted by fluorescing aerosols is performed with ICCD, Intensified Charge Coupled Device. The signal to noise ratio of ICCD devices is smaller by a factor of √2compared to photon counting devices having the same sensitivity. We studied the impact of this difference of signal to noise ratio on the capability of multivariate detection and classification algorithms to operate on various conditions. Signal simulations have been performed to obtain ROC (Receiver Operation Characteristics) Curves and Confusion Matrix to obtain the detection performance and the ability of algorithms to discriminate a potential source from another. Two detection algorithms are used, the Integrated Laser Induced Fluorescence(ILIF) and the Matched Filter. For the classification, three algorithms are used, the Adaptive Matched Filter (AMF), the Adaptive Coherent Estimator (ACE) and the Adaptive Least Squares (ALS). The best algorithm for detection is the AMF using the signature of the material present in a cloud, the ILIF detector performs very well. For the classification, the three algorithms are surprisingly giving the same results for the same data. The classification performs better if the distance between the signatures recorded in a database is important. The performance of the detector and of the classificator improves with an increase of the signal to noise ratio and is consistently and significantly better for the photon counting compared to ICCD.
A standoff sensor called BioSense was developed to demonstrate the capacity to map, track and classify bioaerosol clouds from a distant range and over wide area. The concept of the system is based on a two steps dynamic surveillance: 1) cloud detection using an infrared (IR) scanning cloud mapper and 2) cloud classification based on a staring ultraviolet (UV) Laser Induced Fluorescence (LIF) interrogation. The system can be operated either in an automatic surveillance mode or using manual intervention. The automatic surveillance operation includes several steps: mission planning, sensor deployment, background monitoring, surveillance, cloud detection, classification and finally alarm generation based on the classification result. One of the main challenges is the classification step which relies on a spectrally resolved UV LIF signature library. The construction of this library relies currently on in-chamber releases of various materials that are simultaneously characterized with the standoff sensor and referenced with point sensors such as Aerodynamic Particle Sizer® (APS). The system was tested at three different locations in order to evaluate its capacity to operate in diverse types of surroundings and various environmental conditions. The system showed generally good performances even though the troubleshooting of the system was not completed before initiating the Test and Evaluation (T&E) process. The standoff system performances appeared to be highly dependent on the type of challenges, on the climatic conditions and on the period of day. The real-time results combined with the experience acquired during the 2012 T & E allowed to identify future ameliorations and investigation avenues.
Threats associated with bioaerosol weapons have been around for several decades and have been mostly associated with
terrorist activities or rogue nations. Up to the turn of the millennium, defence concepts against such menaces relied
mainly on point or in-situ detection technologies. Over the last 10 years, significant efforts have been deployed by
multiple countries to supplement the limited spatial coverage of a network of one or more point bio-detectors using lidar
technology. The addition of such technology makes it possible to detect within seconds suspect aerosol clouds over area
of several tens of square kilometers and track their trajectories. These additional capabilities are paramount in directing
presumptive ID missions, mapping hazardous areas, establishing efficient counter-measures and supporting subsequent
forensic investigations. In order to develop such capabilities, Defence Research and Development Canada (DRDC) and
the Chemical, Biological, Radiological-Nuclear, and Explosives Research and Technology Initiative (CRTI) have
supported two major demonstrations based on spectrally resolved Laser Induced Fluorescence (LIF) lidar: BioSense,
aimed at defence military missions in wide open spaces, and SR-BioSpectra, aimed at surveillance of enclosed or semienclosed
wide spaces common to defence and public security missions. This article first reviews briefly the modeling
behind these demonstration concepts. Second, the lidar-adapted and the benchtop bioaerosol LIF chambers (BSL1),
developed to challenge the constructed detection systems and to accelerate the population of the library of spectral LIF
properties of bioaerosols and interferents of interest, will be described. Next, the most recent test and evaluation (T&E)
results obtained with SR-BioSpectra and BioSense are reported. Finally, a brief discussion stating the way ahead for a
complete defence suite is provided.
Standoff detection of explosives residues on surfaces at few meters was made using optical technologies based on
Raman scattering, Laser-Induced Breakdown Spectroscopy (LIBS) and passive standoff FTIR radiometry. By
comparison, detection and analysis of nanogram samples of different explosives was made with a microscope
system where Raman scattering from a micron-size single point illuminated crystal of explosive was observed.
Results from standoff detection experiments using a telescope were compared to experiments using a microscope to
find out important parameters leading to the detection. While detection and spectral identification of the micron-size
explosive particles was possible with a microscope, standoff detection of these particles was very challenging due to
undesired light reflected and produced by the background surface or light coming from other contaminants. Results
illustrated the challenging approach of detecting at a standoff distance the presence of low amount of micron or submicron
explosive particles.
Defence R&D Canada (DRDC) has developed, by the end of the 90s, a standoff bioaerosol sensor based on intensified
range-gated spectrometric detection of Laser Induced Fluorescence (LIF). This sensor called SINBAHD demonstrated
the capability to detect and characterize bioaerosols from a stand-off position. The sensor sensitivity and false alarm rate
directly depend on the background characteristics since these later will dictate the threshold levels to be used. SINBAHD
was used to characterize the background aerosols in a maritime environment close to Halifax, Canada in May 2008. The
characterization of the LIF signal from the background aerosols included spectral, temporal and spatial aspects over 8
nights of continuous data collection. The local environmental conditions in addition to the aerosol concentration and
particle size distribution were recorded during the entire trial period. From the 64 LIF trials, only five showed specific
spectral features. The spectral variability was encountered either at short range, thus closer to the shore, or during a night
having a specific prevalent wind direction. Indeed, the detected anomalies were in most cases directly related to the
climatic conditions. The integrated LIF signal was also processed to assess the use of LIF intensity to identify aerosol
anomalies in a maritime environment.
A standoff bioaerosol sensor based on intensified range-gated spectrometric detection of Laser Induced Fluorescence
was used to spectrally characterize bioaerosol simulants during
in-chamber and open-air releases at Suffield, Canada, in
August 2008 from a standoff position. In total, 42 in-chamber Bacillus atrophaeus (formerly Bacillus subtilis var
globigii; BG) cloud and 27 open-air releases of either BG, Pantoea agglomerans (formerly Erwinia herbicola; EH),
MS2 and ovalbumin (OV) were generated. The clouds were refereed by different point sensors including Aerodynamic
Particle Sizer (APS) and slit or impingers samplers. The APS monitored the particle size distribution and concentration
and the samplers characterized the viable portion of the cloud. The extracted spectral signatures show robustness to
different degree. The correlation assessment showed good results in most cases where the LIF signal to noise ratio was
significant. The sensor 4σ sensitivity was evaluated to 1 300, 600, 100 and 30 ppl for BG, OV, MS2 and EH
respectively. Correlation results are presented by plotting the SINBAHD metric versus the corresponding particle
concentration, in which case, the obtained slope is proportional to the material fluorescence cross-section. The different
acquired signal is hence compared in terms of their fluorescence cross-section additionally to their spectral
characteristics.
We have developed a small, relatively lightweight and efficient short range (<100 m) LIDAR instrument for remotely
detecting harmful bioagents. The system is based on a pulsed, eye-safe, 355 nm laser exciting aerosols which then
fluoresce with a typical spectrum. The system makes use of a novel technology for continuously monitoring for the
presence of unusual concentrations of bioaerosols at a precise remote location within the monitored area, with response
within seconds. Fluorescence is spectrally resolved over 32 channels capable of photon counting. Results show a
sensitivity level of 40 ACPLA of Bacillus Globigii, an anthrax simulant, at a distance of 100 m (assumed worst case
where 1 ppl = 1 ACPLA) considering particle sizes between 0.5 and 10 μm, with a geometric mean at 1 um. The
apparatus has been tested in the field during three test and evaluation campaigns with multiple bioagents and public
security products. Preliminary results show that the system is able to distinguish between harmful bioagents and
naturally occurring ones. A classification algorithm was successfully tested with a single type of bioagent; experiments
for daytime measurements are discussed.
Defence R&D Canada (DRDC) has developed, by the end of the 90s, a standoff bioaerosol sensor prototype based on
intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF) called SINBAHD. This LIDAR
system was used to characterize spectrally the LIF of bioaerosol agent simulants and obscurants during 57 cross-wind
open-air releases at Suffield, CAN in July 2007. An autoclave and gamma-irradiation killing procedures were performed
on Bacillus subtilis var globigii (BG) samples before they were aerosolized, disseminated and spectrally characterized.
Slight discrepancies were observed in the spectral characteristics of killed versus live samples but none between the two
killing methodologies. Significant signature variabilities were observed from the different batches of Erwinia Herbicolas
(EH). The generated cloud was simultaneously characterized in Agent Containing Particle per Liter of Air (ACPLA) by
slit sampler units and in particle per litter of air (ppl) by an Aerodynamic Particle Sizer (APS). Correlation assessment
between the stand-off sensor SINBAHD and the two referee point sensors was done, allowing an estimation of
SINBAHD's sensitivity in ACPLA and in ppl. For a 20-m thick cloud at a range of 990 m, a detection limit of a few tens
of ACPLA and a few ACPLA were obtained for BG and EH respectively. The extracted correlation between ACPLA
and ppl data for releases performed with an agricultural sprayer showed a high degree of variability: 2 to 29% and 1 to
6% of ACPLA/ppl ratio for BG and EH, respectively.
Electro-optic (EO) imaging systems are commonly used to detect civilian and military targets during surveillance
operations and search and rescue missions. Adding the polarization of light as additional information to such active and
passive EO imaging systems may increase the target discrimination performance, as man made objects are known to
depolarized light in different manner than natural background. However, while the polarization of light has been used
and studied in the past for numerous applications, the understanding of the polarization phenomenology taking place
with targets used in cluttered backgrounds requires additional experimentations. Specifically, the target contrast
enhancement obtained by analyzing the polarization of the reflected light from either a direct polarized laser source as
encountered in active imagers, or from natural ambient illumination, needs further investigation. This paper describes an
investigation of the use of polarization-based imaging sensors to discriminate civilian and military targets against
different backgrounds. Measurements were carried out using two custom-designed active and passive imaging systems
operating in the near infrared (NIR) and the long-wave infrared (LWIR) spectral bands. Polarimetric signatures were
acquired during two distinct trials that occurred in 2007, using specific civilian and military targets such as cars and
military vehicles. Results demonstrate to what extent and under which illumination and environmental conditions the
exploitation of active and passive polarimetric images is suitable to enable target detection and recognition for some
events of interest, according to various specific scenarios.
A compact, lab-sized dissemination chamber is designed to characterize the fluorescence of aerosols. The chamber,
designed according to short-range lidar principles, uses light-induced fluorescence (LIF) with a 355 nm pulsed source.
Aerosols concentration inside the chamber can reach hundreds of thousands of ppl. Background noise and irradiance are
very low and will allow accurate measurements of spectral signatures. The chamber will serve to study the correlation
with spectroscopic data obtained using a long-range lidar system owned by Defence Research and Development Canada
(DRDC). Pollens, bacteria, spores, dusts and other atmospheric aerosols will be studied under various environmental
conditions. The chamber will be used to create trustworthy libraries for the remote sensing of bio-aerosols.
An efficient standoff biological warfare detection capability could become an important asset for both defence and security communities based on the increasing biological threat and the limits of the presently existing protection systems. Defence R&D Canada (DRDC) has developed, by the end of the 90s, a standoff bioaerosol sensor prototype based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF). This LIDAR system named SINBAHD monitors the spectrally resolved LIF originating from inelastic interactions with bioaerosols present in atmospheric cells customizable in size and in range. SINBAHD has demonstrated the capability of near real-time detection and classification of bioaerosolized threats at multi-kilometre ranges. In spring 2005, DRDC has initiated the BioSense demonstration project, which combines the SINBAHD technology with a geo-referenced Near InfraRed (NIR) LIDAR cloud mapper. SINBAHD is now being used to acquire more signatures to add in the spectral library and also to optimize and test the new BioSense algorithm strategy. In September 2006, SINBAHD has participated in a two-week trial held at DRDC-Suffield where different open-air wet releases of live and killed bioagent simulants, growth media and obscurants were performed. An autoclave killing procedure was performed on two biological materials (Bacillus subtilis var globigii or BG, and Bacillus thuringiensis or Bt) before being aerosolized, disseminated and spectrally characterized with SINBAHD. The obtained results showed no significant impact of this killing process on their normalised spectral signature in comparison with their live counterparts. Correlation between the detection signals from SINBAHD, an array of slit samplers and a FLuorescent Aerosol Particle Sensor (C-FLAPS) was obtained and SINBAHD's sensitivity could then be estimated. At the 2006 trial, a detection limit of a few tens of Agent Containing Particles per Liter of Air (ACPLA) was obtained for a 15-m thick cloud of live BG located at a range of 400 m.
A compact chamber was developed for the dissemination of biological aerosols. The chamber, measuring 110 cm in length, was designed according to short-range LIDAR principles, and will be used to simulate open-air releases of aerosols. Measurements, carried out by light-induced fluorescence (LIF) techniques, will be correlated with spectroscopic data obtained with a long-range lidar system owned by Defence Research and Development Canada (DRDC). The chamber allows complete control over environmental factors, such as humidity, pressure and temperature, thus facilitating the creation of a trustworthy signature database for the standoff detection of bio-aerosols. Studies will also include the influence of growth stage, stress and growth media on the fluorescence spectra of various biological aerosols.
One of today's primary security challenges is the emerging biological threat due to the increased accessibility to
biological warfare technology and the limited efficiency of detection against such menace. At the end of the 90s, Defence
R&D Canada developed a standoff bioaerosol sensor, SINBAHD, based on intensified range-gated spectrometric
detection of Laser Induced Fluorescence (LIF) with an excitation at 351 nm. This LIDAR system generates specific
spectrally wide fluorescence signals originating from inelastic interactions with complex molecules forming the building
blocks of most bioaerosols. This LIF signal is spectrally collected by a combination of a dispersive element and a range-gated
ICCD that limits the spectral information within a selected atmospheric cell. The system can detect and classify
bioaerosols in real-time, with the help of a data exploitation process based on a least-square fit of the acquired
fluorescence signal by a linear combination of normalized spectral signatures. The detection and classification processes
are hence directly dependant on the accuracy of these signatures to represent the intrinsic fluorescence of bioaerosols and
their discrepancy. Comparisons of spectral signatures acquired at Suffield in 2001 and at Dugway in 2005 of bioaerosol
simulants, Bacillius subtilis var globiggi (BG) and Erwinia herbicola (EH), having different origin, preparation protocol
and/or dissemination modes, has been made and demonstrates the robustness of the obtained spectral signatures in these
particular cases. Specific spectral signatures and their minimum detectable concentrations for different
simulants/interferents obtained at the Joint Biological Standoff Detection System (JBSDS) increment II field
demonstration trial, Dugway Proving Ground (DPG) in June 2005, are also presented.
The biological threat has emerged as one of today's primary security challenges due to the increased accessibility to biological warfare technology and the limited efficiency of detection and protection measures against such menace. Defence Research and Development Canada (DRDC) has investigated various methods, including the improvement of atmospheric bioaerosol monitoring, to increase the readiness against such threat. By the end of the 90s, DRDC developed a standoff bioaerosol sensor based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF). This work has showed an important potential of detecting and discriminating in real-time several bioaerosols. The LIDAR system that monitors atmosphere cells from a standoff position induces specific spectrally wide fluorescence signals originating from inelastic interactions with complex molecules forming the building blocks of the bioaerosols. This LIF signal is spectrally collected by a combination of a dispersive element and a range-gated ICCD that records the spectral information within a range-selected atmospheric volume. To assess further the potential of discrimination of such technique, this innovative sensor was used to obtain spectral data of various natural bioaerosols. In order to evaluate the discrimination of biological agent simulants from naturally occurring background fluorescing materials, the obtained results were compared with the ones of bioaerosol simulants (Bacillius subtilis var globiggi (BG) and Erwinia herbicola (EH)) acquired in 2001. The robustness of the spectral data with time was also investigated. From our results, most of the studied natural materials showed a spectral shift of various degrees, and up to 10 nm, to the longer wavelength one year later.
We measure the cross-polarized backscattered light from a linearly polarized laser beam penetrating a cloud made of spherical particles with a gated intensified CCD camera. In accordance with previously published results, we observe a clear azimuthal pattern in the recorded images. We show that the pattern originates from second order scattering, and that higher-order scattering causes blurring that increases with optical depth. We also find that the contrast of the symmetrical features can be related to the measure of the optical depth. Moreover, by identifying and subtracting the blurring contributions, the resulting pattern provides a "pure" second-order scattering measurement that can be used for the retrieval of droplet size. We apply this technique on a stratus cloud located at 1400 m. The extinction values retrieved on the basis of the laboratory quantification of the blurring of the multiple scattering secondary polarization patterns measured from the ICCD images are then compared with the profile of the extinction coefficient obtained using Bissonnette's algorithm, which is based on the multiple-field-of-view (MFOV) lidar returns.
Hyperspectral imaging has demonstrated impressive capabilities in airborne surveys, particularly for mineral and biomass characterizations. Based on this success, it is believed that other applications like search and rescue operations, and detection/identification of various ground military targets could greatly benefit from this technology. The strength of hyperspectral imaging comes from the access to another dimension of information: the spectral content of the detected return signal for each spatial pixel. In the case of conventional hyperspectral imaging, the return signal depicts the spectral reflectance of the day irradiance from the scene within the field of view of each pixel. However, by inserting a range-gated intensifier into a hyperspectral camera and by combining the camera with selected pulsed lasers, it becomes possible to relate the returned spectral information to specific light/matter interactions like induced fluorescence. This new technique may be referred to as 'active hyperspectral imaging.' Among its advantages, this approach is independent of the ambient lighting conditions and can be customized in excitation wavelengths. Moreover, by using a range-gated intensified camera, it is possible to survey limited area with a significant increase in signal-to-noise ratio. A camera of this type has been built by our group in collaboration with private industry and is described in this paper. The internal design of the camera is discussed, new issues concerning the calibration of the camera are depicted and a model based on signal-to-noise ratio analysis is presented. From the fluorescent characteristics of surrogate land mines measured in the laboratory, this model is used to predict the capabilities of detecting surface-laid mines from an aerial platform based scenario.
Search and rescue and general surveillance mission pose a serious challenge to conventional imaging systems used by actual aircraft crews. These systems must often work in low- light and low-visibility conditions to find the identify targets. A new airborne imaging technology has been developed to overcome several deficiencies encountered with common CCD cameras, image intensified system and thermal imaging sensors. The recent developments in laser diode arrays, laser diode beam collimation and gatable micro- channel plate intensifier have made possible the construction of a compact active imagin system, called the Airborne Laser-Based Enhanced Detection and Observation Systems (ALBEDOS). This system proved particularly efficient at night and in degraded weather conditions. In addition, it was demonstrated that range gating, besides eliminating most of the light backscattered by aerosols, provided to some extent immunity to blooming effects specific to highly sensitive cameras. The system was installed on a helicopter and tested in various scenarios in October 1995 to demonstrate its potential. To enhance the surveillance capability over large areas of coverage, to optimize detection of humans and small objects and to improve the effectiveness of the search aircraft, a second-generation payload is presently developed and combines the benefits of two complementary imaging sensors. The Enhanced Low-Light level Visible and IR Surveillance System (ELVISS) consists of an improved range-gated active imager and a high-quality thermal imager, installed in two separate airborne platforms slaved together and controlled by a single user interface. It is expected that such a sensor systems will have a direct impact on improving the response time in finding those in need of assistance or simply in increasing the performance, reliability and efficiency of crews involved in general surveillance operations. This paper explains the concept of range gating, details a preliminary performance model and describes the two generations of Canadian active imagers: ALBEDOS and ELVISS.
In atmospheric sensing, one application that has demonstrated several impressive successes over the last two decades is LIght Detection And Ranging (LIDAR). With elastic signal returns, this technique remotely provides information such as the particle density and, for a multiple field of view LIDAR, the distribution in size of the aerosols as a function of the range along the probing laser beam. For this type of application, the return signal has the same spectrum than the laser source. Some specific techniques, such as Raman or resonant LIDARs, collect the return signal at wavelengths other than the source. However, these signals are usually narrow spectrally and are collected with a single bandpass spectral filter. Recently, the Canadian Defence Research and Development Branch has initiated the evaluation of a novel LIDAR concept which opens the possibility of collecting simultaneously the detailed spectral information contained in spectrally wide return signals. One drawback with this approach is the loss of simultaneous information at multiple ranges, i.e., the spectral information is available only for a specific range. Nevertheless, there are applications where the partial loss of range information is compensated by the gain resulting from the spectral information. This paper describes the concept and reviews the general model predicting the capability of this technique for the standoff detection of bioaerosols. It shows a numerical simulation of the anticipated spectral profiles collected with the proposed active range-gated fluorescent LIDAR for a particular bioaerosol as a function of ranges, and for both day and night operational scenarios.
The Defense Research Establishment, Valcartier has an ongoing project on a multi-sensors system, called CAMUS (Common Aperture MUlti-Sensors). The main objective of this project is to demonstrate the concept of fusing three sensors on a single chassis. The project covers the development of the sensors' head and the processing sub-systems required for fusing the acquired data and information. The three sensors identified for this project are: a visible camera, a 3 - 5 micrometer infrared camera and a 94 GHz millimeter-wave radar. This paper describes the approach used to combine the three sensors along with the various processing schemes to merge the visible and infrared images with the radar information. The CAMUS system will present all the information gathered by the three sensors on a single display to the operator. The main application of this project is to demonstrate an advanced sight for a direct fire control system.
In minefield detection, two main types of operation can be identified. First, there is the detection of surface-laid minefield. This scenario is encountered largely in tactical operations (troop movement, beach landing) where the speed at which the minefield is deployed or the strategic barrier that they represent exceed the need to bury them. Second, there is the detection of buried minefield which is encountered mainly in peacekeeping missions or clearance operations. To address these two types of minefield detection process, we propose an airborne far-infrared minefield imaging system (AFIRMIS). This passive and active imaging system fuses the information from the emissivity, the reflectivity and the 3-dimensional profile of the target/background scene in order to improve the probability of detection and to reduce the false alarm rate. This paper describes the proposed imaging system and presents early active imaging results of surface-laid mines.
All systems operating in the visible and infrared bands of the spectrum are subject to a severe performance degradation when used in adverse weather conditions like fog, snow or rain. This is particularly true for active systems as rangefinders, laser designator, lidars and active imaging sensors where the laser beam will suffer attenuation, turbulence and scattering from the aerosols present in the atmospheric path. This paper presents the ALBEDOS active imaging performance in fog which was determined by observing reference targets through a 22-m controlled-environmental chamber, where fogs with various densities and droplet sizes were generated in a calibrated manner. ALBEDOS is an acronym for Airborne Laser-Based Enhanced Detection and Observation System and is based on a compact, powerful laser diode illuminator and a range-gated intensified CCD camera. It is capable of detecting and identifying people or objects in complete darkness and, to some extent, in adverse weather conditions. In this paper, we compare the efficiency of the range-gated active imager in fog with those of a far-infrared thermal imager and of a low-light level camera operating in a continuous mode.
KEYWORDS: Mining, Roads, Land mines, Temperature metrology, Cameras, Thermal effects, Data modeling, Soil science, Defense and security, Infrared cameras
In order to reduce the serious problem associated with the mining of important supply/communication roads by hostile parties during peacekeeping operations, the Canadian Department of National Defense has recently begun the development of a multi-sensor teleoperated mine detection vehicle, the Improved Landmine Detection Capability. One sensor identified as a serious candidate for that project is a passive IR camera. In the past, many organizations have assessed the efficiency of this technique of detection and reported widely fluctuating results. It is believed that the main reason for these fluctuations is associated with the ad hoc interpretations used by different researchers. In this paper, a more systematic analysis is presented which takes into account variables such as time of the day, time of the year, weather conditions, type of road and many others. A working model is proposed in order to facilitate the prediction of the IR signature of the buried land-mine and is compared with data acquired from multiple trials. These trials were done with live mines (without fuzes) and surrogates buried in different types of road (packed gravel and sand) and during different times of the day and different times of the year.
KEYWORDS: Modulation, Carbon dioxide lasers, Mining, Imaging systems, Speckle, Mode locking, Signal detection, Signal processing, Land mines, Long wavelength infrared
When choosing a route to transport troops and equipment in tactical scenarios, one requires a decision-making scheme that can make fast surveys of the possible paths. One of the main threats in this operation is the presence of scattered surface-laid mines. A possible solution would use an airborne long wave infrared (LWIR) active imaging system. In this paper, we report on one such system based on an intensity modulated waveguide CO2 laser. This system, which provides images in reflected intensity and relative range, has been tested on replica mines in laboratory. A relative range resolution of 2 mm is reported. Evidence of the insensitivity to the contrast in reflection and the absence of speckle noise for the relative range images is shown. A phenomenon associated with the erroneous evaluation of the relative range of inclined surfaces is identified.
For scanning active imaging systems using direct detection, it is possible to adequately model the expected speckle noise. Modifications are introduced to the theory on speckle originally proposed by Goodman to take into account the scanning effect. The model presented here is verified experimentally for a scanning active imaging system using a CO2 laser (10.6 μm). A direct relation between the reduction in the speckle noise resulting from the scanning process and the imaging resolution is demonstrated.
Submicron etched and diffused gratings are produced on ionexchanged
glass waveguides. Efficient interaction between the guided
light and the grating is observed. Propagation properties of these
components are thoroughly investigated.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.