We present imaging results of a ground penetrating radar (GPR) dataset collected for permafrost studies at the APEX (Alaska Peatland EXperiment) BETA site, which is located approximately 30 miles southwest of Fairbanks, Alaska. The measurements were collected in an out-and-back style survey using a dual-frequency GPR with ultra-wide bandwidth centered at 170 MHz and 600 MHz. At each center frequency, we employ both conventional frequency-domain backprojection method and a sparse reconstruction technique with total variation minimization for subsurface image formation. As the latter minimizes the image gradient, it provides better edge preservation and improved reconstruction of extended targets, such as the permafrost table, compared to backprojection. We explore fusion of dual-frequency and dualscan subsurface images and compare performance of various combinations of image formation and fusion methods in terms of enhanced detection of the top of the permafrost table.

This work reports the potential of first-order, non-autonomous chaotic circuits for bistatic radar applications. Unlike most chaotic systems, 1st order chaotic systems offer closed-form analytic solutions that aid in designing simple matched filters. In this work, a signal generated by a 1st chaotic oscillator is transmitted towards both the receiver and the target, enabling the use of this waveform for two purposes. First, the waveform serves to synchronize the bistatic radar receiver. Second, the waveform assists in acquiring an estimate of the target’s range. For the first time, we show that two 1st order chaotic circuits can be synchronized using a simple resistive coupling. The cross-correlation between the two synchronized circuits is of high quality, exhibiting a narrow main lobe width and low sidelobe levels. Consequently, these 1st order systems can generate high-range resolution profiles in bistatic configurations. Lastly, analytical expressions show that the cross-ambiguity function between the echo received from the target and synchronized waveforms yields a near thumb-tack shape, emphasizing the value of a noise-like waveform for radar-ranging applications.

Subwavelength resonant lattices fashioned as nano- and microstructured films represent a basis for a host of device concepts. Whereas the canonical physical properties are fully embodied in a one-dimensional periodic lattice, the final device constructs are often patterned in two-dimensionally-modulated films in which case we may refer to them as photonic crystal slabs, metamaterials, or metasurfaces. These surfaces can support lateral modes and localized field signatures with propagative and evanescent diffraction channels critically controlling the response. The governing principle of guided-mode, or lattice, resonance enables diverse spectral expressions such that a single-layer component can behave as a sensor, reflector, filter, or polarizer. This structural sparsity contrasts strongly with the venerable field of multi-layer thin-film optics that is basis for most optical components on the market today. The lattice resonance effect can be exploited in all major spectral regions with appropriate low-loss materials and fabrication resources. In this paper, we highlight resonant device technology and present our work on design, fabrication, and characterization of optical elements operating in the near-IR, mid-IR, and long-wave IR spectral regions. Examples of fabricated and tested devices include biological sensors, high-contrast-ratio polarizers, narrow-band notch filters, and wideband high reflectors.

Surveillance radar systems equipped with active electronically scanned antenna arrays (AESA) typically operate with low spatial resolution (50 to 100 m). Under these conditions, the data transformation from the radar signal in the frequency, array position and slow time dimensions to the reflectivity map in the range, angle and Doppler dimensions is conventionally performed by a 3-D fast Fourier transform (FFT). In this paper, we consider a radar system equipped with a wide, near-field array, providing high angular resolution, and examine the changes required in the matched filter-based signal processing to accommodate this sensing geometry. Beamforming techniques that include exact, approximate, FFT-based and sparse-array-based matched filter implementations are investigated. Additionally, we consider joint Doppler-azimuth mapping with wide antenna arrays, while the system operates with narrowband waveforms to allow decoupling of range from the other two signal dimensions. In the numerical examples, we demonstrate a 200-m-wide, S-band sparse array capable of achieving 0.03° resolution in azimuth. Processing with a fully coupled, high range resolution system equipped with a wide antenna array will be investigated in a future publication.

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This paper outlines opportunities and challenges for building missile seekers with the Sensor Open Systems Architecture^TM (SOSA) Technical Standard, Edition 2.0, Version 2 (Snapshot 2). In Section 1, two missile seeker instance architectures using the SOSA Technical Architecture are described, one for Electro-Optical/Infrared (EO/IR) and one for Radio Detection and Ranging (RADAR). Opportunities within the logical signal processing chain, including module functions, inter-module interactions, and messaging sets are discussed in Sections 2, 3, 4, and 5. Section 6 addresses the potential challenges in the physical layer due Size, Weight, and Power (SWaP) constraints on missile systems. In Section 7, some opportunities to support swappable seekers within the Modular Open Systems Approach (MOSA) ecosystem are outlined. The findings of this effort are summarized in the conclusion section.

Remote sensing from and communications through vegetation and forests requires accurate modeling and understanding of electromagnetic wave propagation through those environments. Specifically, the coherent summation of the electromagnetic waves due to both the single scatter and multi-scatter effects must be evaluated. To accurately perform this evaluation, the Body of Revolution (BOR) Method of Moments must be extended to accept non-plane wave incidence fields on the Body of Revolution. This report performs an analytical derivation for non-plane wave incident fields, examines a Hertzian dipole field incident on a Body of Revolution, and validates the scattered field results with a commercial 3-D Method of Moments code.

The recursive sidelobe minimization (RSM) algorithm is an iterative method that relies on the incoherent nature of sidelobes to iteratively attenuate them in radar imagery. Grating lobes are points of coherence that arise when a periodic aperture does not satisfy the Nyquist sampling rate. Grating lobes are coherent, so the RSM algorithm cannot iteratively attenuate them in the same manner as sidelobes. Random sampling reduces coherency in resolution cells where targets are not present, and greatly increases the sidelobe energy throughout the imagery. In this paper, random sampling is combined with the RSM algorithm to generate 3-dimensional (3-D) imagery with sparse 2 D apertures. The random aperture sampling avoids the creation of grating lobes, but greatly increases the sidelobe levels throughout the image. Then the RSM algorithm is applied to reduce the sidelobes. This technique is first applied to a simulated point target. Then, it is applied to modeled and experimental data to demonstrate its efficacy with extended targets.

This work investigates the detection of targets in an unknown complex scene by means of an ad hoc network of widely distributed sensors that are spread over the region of surveillance. A general coherent change detection methodology is developed that is based on the classical optical theorem of wave scattering theory. It relies on spatial-temporal-spectral projections of the scattered field data onto the incident field or background medium response data. This involves only data gathered in situ by the sensing array. Thus the proposed approach is purely data-driven, an important property for application in unknown media. Another important feature is that the derived approach admits alternative hardware and software implementations and this flexibility can be adopted to enhance resilience to interference and eavesdropping. The performance of the optical-theorem-based detection method is discussed. It is shown that it outperforms existing methods for change detection such as the classical energy detector under certain coherence conditions or views of the imaging system. The derived theory and algorithms are illustrated with computer simulations.

The emergence of 5G networks in frequency bands close to those used by aviation radar altimeters introduces new interference challenges, necessitating innovative solutions for accurate altitude prediction. This paper introduces a novel approach using machine learning (ML) algorithms to predict aircraft altitude from down sweep signals of frequency-modulated continuous wave (FMCW) radar altimeters, focusing on overcoming 5G interference. It details the implementation of various ML models and the use of down sweep data, which provides unique signal characteristics advantageous for altitude estimation. The methodology involves collecting and processing real 5G signals, emulating radar altimeter operation under different interference levels to create a comprehensive dataset, and rigorously evaluating the ML models with statistical metrics to verify their accuracy in altitude prediction amidst 5G signals. The results show that this ML-based framework markedly enhances altitude estimation accuracy, offering a robust method for radar altimeter operation in the 5G era. This research advances flight safety by providing a solution for reliable altitude measurement despite potential 5G interference.

In synthetic aperture radar theory, periodic spatial sampling that satisfies Nyquist theorem can be used to generate imagery with minimal ambiguities. A two-dimensional (2-D) grid of uniformly spaced aperture samples can be used to generate three-dimensional (3-D) radar imagery. However, 2-D apertures typically result in an untenable number of samples for practical implementation. The spacing between aperture samples can be increased to reduce the number of samples at the potential cost of introducing ambiguities. Since the sampling is uniform, this can introduce grating lobes within the image area. Grating lobes are erroneous points of coherence that result from sub sampling (i.e., not satisfying Nyquist theorem) a periodic array. The recursive sidelobe minimization (RSM) algorithm removes sidelobes by exploiting the varying null positions in images formed with random subapertures. However, grating lobe spacing is generally unaffected by subaperture selection in periodic arrays. This paper presents a modification to the RSM algorithm which removes grating lobes by randomizing the operating center frequency for each iteration of the algorithm.

Nonlinear radar technology has been employed in various applications for a few decades, primarily focusing on second-order harmonic radar systems. This study delves into the potential benefits and drawbacks of utilizing higher-order harmonic radar systems. We present a comparative analysis between second- and third-order harmonic systems using Cadence AWR Visual System Simulator (VSS) followed by experimental validation. In the experiments, target emulation is achieved through nonlinear tags. In contrast, cluttered environments near the targets are simulated using corner reflectors, with the tag and the corner reflector moving at different frequencies facilitated by Zaber linear actuators. Our findings reveal both the advantages and limitations associated with higher-order systems, offering valuable insights into an underexplored area of research within the domain of harmonic radar technology. This contribution addresses the existing gap in the literature pertaining to higher-order harmonic radars by providing comparative analyses using both measurement and simulation data.

Wireless ranging and positioning plays a pivotal role across numerous applications, encompassing wireless networks, robotics, navigation, and distributed wireless systems. A common limitation encountered in many ranging algorithms relates to the requirement for waveforms with sufficiently wide bandwidth to attain precise ranging accuracy. In this study, we investigate the applicability of orthogonal frequency-division multiplexing (OFDM) signals for microwave-ranging without necessitating any modifications. OFDM, being a joint communications and sensing waveform, offers the advantage of repurposing existing communication signals for ranging purposes without additional spectrum utilization. We discuss the theoretical underpinnings of our investigation and present simulated and experimental ranging measurements employing OFDM signals, complemented by range estimation and error analyses.

The survivability of small Unmanned Aerial Systems (sUAS) in high-intensity electromagnetic environments (HIRF) is a significant characterization that determines the capabilities of UAS in critical operation situations. The existing small UAS system designs do not consider the complexity of adversary electromagnetic environments, such as Radio Frequency (RF) interference, electromagnetic interference (EMI), Counter-UAS (C-UAS) electromagnetic attack (EA), and other nearby sources of noises in spectrums. This study aims to determine the feasible approaches that support the “hardening” of the existing S-UAS to counter or mitigate the impacts of HIRF and evaluate such improvements in both laboratory environments and flight tests. The first step is to identify the weak spots of the existing flight vehicles, from the propeller, motors, and controllers, as well as the internal electronics, especially the RF radios and power supplies. The second step is to emulate the HIRF environment we expect in multiple domains (such as air, sea, or ground airport) in laboratory environments. We are introducing a lab-based emulation testbed with higher power and better configurations than the previous work and installed it for the new emulation experiments. Thirdly, we perform careful power level measurements and calibrations and compare them to the theoretical models. The system setup and size focus on the S-band (near Wi-Fi band) radio links, electronic components, onboard GPS, and navigational sensors. At the same time, the same approach can be easily extended to other frequencies. From this study, we introduced three levels of mitigation measures. (1) Minimal protection. (2) Shielding solution. (3) Shielding and EMI filtering solution. We demonstrated how these levels of mitigation solutions affect the risk levels of survivability in the HIRF environments near high-power radars.

To prevent accidents caused by collapse and rockfall tunnel faces during construction, we considered vibration monitoring using a millimeter-wave (78-GHz band) DBF-based high-speed imaging radar. Basic performance tests were conducted in a radio anechoic room and test facility simulating an actual tunnel. It was confirmed that the accuracy of the 0.1-mm displacement-measurement, high-speed sampling of 0.001 s, and individual movements of several targets could be distinguished. Based on the basic test results, on-site measurements were performed at an actual tunnel construction site. The displacement and vibration changes of a tunnel face at the time of breakthrough can be captured; in addition, large velocity changes occur in a working face before breakthrough, and it might be possible to detect an abnormal tunnel face in advance. In addition, it was confirmed that the movement of the rockfall location was almost precisely captured even for small-scale flaking during the drilling of the working face, regardless of the condition in which a part of the measurement range became shadowed.

Common target tracking algorithms, such as the Kalman Filter, assume Gaussian estimates of process and measurement noises. This Gaussian assumption does not fully support practical maneuvering target tracking. Rather, when target motion is highly dynamic, sudden maneuvers are better described by non-Gaussian noise distributions. A Kalman-Levy filter has been proposed as an improvement to the maneuvering target tracking problem. This filter models process and measurement noises using Levy distributions. While an improvement in maneuver estimation is demonstrated with the Kalman-Levy filter, it requires significant computation time and occasionally provides poor estimates of simple, linear maneuvers that the Kalman filter can otherwise provide. This paper seeks to improve maneuvering target tracking without sacrificing computation time by proposing the use of a moving-average filter in the tracking process. A Moving-Average filter is used to track the position root-mean-square error (RMSE) and switch from the Kalman filter to the Kalman-Levy filter when this error becomes large. The Kalman filter, the Kalman-Levy filter, and the switching algorithm based on the Moving-Average filter are demonstrated on two tracking problems. Simulation results show that switching between the filters improves maneuvering target state estimation accuracy while being computationally efficient.

Cognitive radar systems are radar systems that can self-adjust themselves to respond to changes in the environment. Developing cognitive radar systems relies on their ability to detect these changes in operational conditions and use this knowledge to change the operating characteristics of the system, to optimally solve a selected task. Engineers must have an expert level knowledge of radar systems in order to solve these problems as they arise. The goals of the system can be easily stated to engineers in the form of natural language, but are very difficult for computers to analyze. Previous work has shown that Natural Language Processing (NLP) models can be developed to extract radar parameters, values, and units from text. Language Based Cost Functions (LBCFs) can then utilize this extracted information to develop constraints on specific radar parameters. In this work, we propose to combine these language models with LBCFs to define a objective function for optimization tasks using natural language.

Cutting-edge personnel security screening relies on microwave imaging, where addressing future security demands entails integrating digital twins into development and testing processes. To create a realistic digital twin for microwave imaging systems, accurate replication of microwave images obtained from scanning real individuals is crucial, achieved through electromagnetic simulation. Employing fast simulation methods reduces the computational load to a viable level, yet it introduces some computational inaccuracies due to underlying approximations. The extent to which these inaccuracies affect microwave images is often unclear, while digital twins are already being used. To thoroughly assess this unknown influence, the simulation results obtained with physical optics (PO) and geometrical optics (GO) are compared with an integral equation (IE) solution approach using two scenarios of a walk-through personnel security screening in the frequency band below 10.6 GHz. Remarkably, while radar images are highly similar, raw signals exhibit significant deviations. Thus, for radar image simulation, PO and GO appear sufficiently accurate, offering attractive runtimes below two minutes per simulation. Conversely, the IE method proves impractical in many situations, as a single image necessitates over three weeks of computations.

Two current hurdles of quantum RADAR/LiDAR technology are i.) The use of joint measurement techniques, whereby the idler remains in a delay line or a quantum memory to be measured later with the returning signal, and ii.) The difficulty in creating high photon flux signals for long range sensing. Our measurement and detection protocol using immediate-idler-detection (IID) helps to alleviate both of these issues. We present our recent experimental data from characterizing our proof-of-concept IID quantum LiDAR system and show that similar to delay line approaches, we achieve strong correlation even in extremely noisy channels where the noise level exceeds the signal strength by as much as one hundred times. We have found that even in very lossy channels, the integration time remains extremely short and roughly the same value even as the noise is increased. We also show preliminary results through foggy free space channels and found positive correlation SNR even when the visibility was as low as 15%. Our measurement and detection protocol was designed to align closely with classical RADAR and LiDAR signal processing to better align the quantum and classical sensor regimes and allows for the potential to scale upwards and produce higher photon-flux signals from multiple photon pair sources.

Quantum radars are garnering increasing attention, but one class of quantum radars has not received very much attention: quantum interferometric radars. Such radars use a type of entangled quantum signal called N00N states to enhance phase sensitivity. In this paper, we propose that quantum interferometric radars could be used for biomedical applications such as vital signs monitoring and organ imaging. Due to such radars being able to operate well at low transmit powers and the radiation itself being non-ionizing, they can mitigate any safety risk to patients.

We describe a sensing scheme that, by designing a transmitter array and a single receiver antenna, potentially resolves the low-power limitation that has plagued previous quantum illumination protocols. Despite the interference among different returning signals, we provide two measurement protocols, one based on parametric amplification, and one based on the recently proposed correlation-to-displacement conversion to achieve a quantum advantage in multiparameter estimation and hypothesis testing.

Vescent has developed a prototype ultra-stable microwave photonic oscillator capable of advancing the dual DoD and non-DoD needs for alternative positioning, navigation and timing (aPNT), multi-static synthetic aperture radar (SAR), 5G-and-beyond wireless communication, satellite synchronization, and geodetic sensing. Due to shortcomings in sensitivity, dynamic range, and/or resolution, current microwave oscillators for radar limit the identification and tracking of objects with small radar cross sections, including slow-moving objects such as drones. These limitations are dominated by the microwave oscillator phase noise and/or instability. Vescent’s photonic microwave source exploits the method of optical frequency division to transfer the pristine phase noise properties of an ultranarrow linewidth optical laser to microwaves in the L-, C-, or X-band for sensing and imaging. Efforts to improve the long-term frequency stability required in communications and timing synchronization will be discussed. The environmental performance of several key subsystems will also be considered with pathways to reduced size, weight, and power (SWaP). Finally, performance improvements related to the long-term stability of this system will be discussed to simultaneously provide both ultralow phase noise comparable to the best deployable microwave oscillators available and low frequency instability for communication and timing synchronization at a drastically reduced SWaP and environmental susceptibility.

In this paper, we report the results of a radar and accelerometer based pilot observational study of gait patterns of elderly participants enrolled in an exercise program aimed at improving strength, balance, and agility. We employ a radar system and a wearable accelerometer device to capture biomechanical movements of the participants as they walk back and forth in front of a radar. We extract gait parameters by analyzing the Doppler signatures obtained from the radar measurements and time-series data from the accelerometer device worn on the wrist while walking. Additionally, we record physical activity levels of participants over a two-week period using the wrist-worn accelerometer device and determine duration of moderate-to-vigorous physical activity (MVPA). The gait parameters and MVPA duration, extracted from two separate sets of measurements made prior to and at the conclusion of the exercise program, are used to assess potential changes in the gait and mobility of the participants. Using percentage change in parameter values as a metric, the results generally demonstrate a positive impact of the exercise program on gait and physical activity levels. At the same time, an appreciable categorical agreement is observed between the two sensing modalities.

Human activity recognition (HAR) with radar-based technologies has become a popular research area in the past decade. However, the objective of these studies are often to classify human activity for anyone; thus, models are trained using data spanning as broad a swath of people and mobility profiles as possible. In contrast, applications of HAR and gait analysis to remote health monitoring require characterization of the person-specific qualities of a person’s activities and gait, which greatly depends on age, health and agility. In fact, the speed or agility with which a person moves can be an important health indicator. In this study, we propose a multi-input multi-task deep learning framework to simultaneously learn a person’s activity and agility. In this initial study, we consider three different agility states: slow, nominal, and fast. It is shown that joint learning of agility and activity improves the classification accuracy for both activity and agility recognition tasks. To the best of our knowledge, this study is the first work considering both agility characterization and personalized activity recognition using RF sensing.

Micro-Doppler radar is a cutting-edge technology that has revolutionized the field of radar sensing to enable the detection and characterization of complex targets by leveraging their micro-motion dynamics. This paper discusses the design and construction of a 10-GHz continuous wave (CW) micro-Doppler radar, an explanation of how the system operates and extracts data, as well as a discussion of the device’s possible applications for characterizing external vibrations of vehicles under different scenarios. The objective is to highlight the potential of micro-Doppler radar for remotely recognizing vehicle transmission shifts and occupancy.

In recent years, the recognition and analysis of human gaits have garnered significant interest in diverse applications such as biometrics, healthcare, and security. This paper presents a simulation study and analysis of limps of different severities and comparison with normal walking gait. Various limp gaits were simulated by adjusting some of the parameters in a well-known gait model developed for normal gait. Analysis was performed by extracting various metrics using the micro-Doppler features as well as the Hilbert-Huang model, which show differences for limping stages. It is conjectured that by combining micro-Doppler features with specific metrics derived from HHT analysis, it may be possible to detect the onset of limp gait and to assess its severity.

Presently, there are no published national or international consensus standards for measuring the image quality of active millimeter wave (MMW) systems, despite the wide adoption of these systems for security screening of passengers in aviation security. To help fill this standards gap, a working group of MMW stakeholders was formed to develop an open, consensus standard for measuring the image quality of active systems employing the 3 GHz to 150 GHz frequency range. The soon-to-be-published standard, IEEE N42.59, describes test objects, test methods, and objective analysis algorithms for measuring several aspects of image quality. This paper describes the lateral spatial resolution test. A method is described for estimating the modulation transfer function by Fourier analysis of images of bar patterns and example images, analysis methods, and results are given.

Structural materials that are virtually invisible during millimeter-wave imaging are needed for applications in testing Advanced Imaging Technology (AIT) screening systems, for example by supporting image-quality test objects. Laboratory measurement of the electrical permittivity of candidate materials at the frequency of the imaging system can appraise their suitability as very low-reflective materials, but measurement is challenging because the ideal material has a real component of permittivity near unity and nearly zero propagation loss. A method is described based on temporal features in wave packet propagation using dual calibrations for front and back interfaces. Measurements of different foam materials are demonstrated.

Millimeter-wave imaging is attracting increasing interest due to the non-ionizing nature of millimeter-wave radiation and the benefits that it entails for various emerging applications. This work uses a low-cost radar architecture that scans a commercial V Band multiple-input multiple-output (MIMO) radar sensor in several locations to synthesize a larger radar aperture. This paper presents the image reconstruction of two targets placed in different ranges with limited scanning and reduced aperture size to overcome the high overall system cost and weight associated with traditional multi-element apertures. We show simulated and experimental measurements by utilizing a 20TX/20RX single-board radar from 62 to 67 GHz.

An active 3D microwave / millimeter-wave shoe scanner was previously developed at the Pacific Northwest National Laboratory (PNNL) using two linear arrays scanned over a rectilinear aperture. The radar system chirps a frequency sweep from 10-40 GHz. These frequencies allow imaging through optically opaque material such as leather, rubber, plastics, and other dielectrics. The system was designed to detect concealed items in the soles of shoes while allowing people to leave their shoes on through a security checkpoint. To shrink the footprint of the system, a new iteration of the design has been developed that scans the two linear arrays over a circular aperture. This new footprint opens the possibility of it being installed in the floor of a cylindrical millimeter-wave body scanner. The backprojection-based multilayer dielectric image reconstruction developed at PNNL can easily handle arbitrary spatial sampling, accommodating the new rotational shoe scanner design. Commonly, the fast Fourier transform (FFT) is used to efficiently compute the range response from the data collected by the system as a preprocessing step to the backprojection algorithm. It was found that converting to range using the discrete Fourier transform (DFT) directly has some advantages over the FFT. For example, nonlinear and non-uniform frequency sweeps can easily be compensated for during the computation of the DFT and only the range bins of interest need to be computed and their spacing can be chosen arbitrarily. Because the range conversion step of the image reconstruction is the fastest part of the process there is very little speed penalty for using the DFT over the FFT and it can even increase the speed of image reconstruction when the ranges of interest are fewer than the total span that is calculated in the FFT.

The Pacific Northwest National Laboratory (PNNL) has recently developed a next-generation cylindrical millimeter-wave imaging system. This system is based on linear sparse multistatic imaging arrays. Data from this system can be focused using 3D FFT-based reconstruction algorithms, which are reasonably efficient and can be performed in near real time, or by back-projection methods that are versatile and more accurate but are computationally intensive and require lengthy post-processing. Cylindrical Fast Backprojection (CFBP) is a novel image reconstruction algorithm developed at PNNL that radically increases the efficiency of backprojection and is ideally suited to microwave and millimeter-wave imaging systems based on scanned linear arrays such as body scanners in common use for aviation security screening. This method achieves its gains in efficiency by separating a full backprojection into a sequence of three steps, range focusing, vertical focusing, and lateral focusing, with intermediate results used to avoid repetitive multidimensional computation. The method is called cylindrical fast backprojection due to the use of two-dimensional stored results, or look-up tables, that have cylindrical symmetry about the linear array. The method is well suited to cylindrically scanned linear arrays but is equally valid for linear arrays scanned to form planar or arbitrary apertures. This paper describes the CFBP algorithm and validates its performance using simulated data.

Millimetre-wave radar is expected to enable imaging radar by improving spatial resolution. However, this is difficult to realize in commercial ICs due to the small number of antennas. Expanding the aperture size by cascading commercial ICs complicates the module design. In addition, the accuracy of DoA estimation for short-range targets is degraded. We therefore propose a method to simultaneously improve spatial resolution and mitigate DoA estimation degradation by simply arranging multiple modules with a single IC, and present experimental results.

Millimeter-wave (mm-wave) imaging systems are proving to be critical in high-resolution imaging to enable automatic security screening applications. In this article, we introduce a novel K-band computational imaging system that integrates custom-designed metasurfaces with shape-morphing origami platforms to enable scene adaptive imaging. The system comprises of metasurface-based active transceivers operating at frequencies ranging from 17 to 27 GHz mounted on a shape morphing origami platforms to demonstrate diffraction-limited reconstruction of 2D and 3D targets. This approach is scalable, modular, conformable, and cost-effective. Furthermore, we exploit information-theoretic techniques based on the Shannon-Hartley theorem to analyze measurements and reconstruct scenes, which in turn provides a mathematical basis to the formal design of such imaging apertures.

Georegistration of synthetic aperture radar (SAR) images is an ongoing problem. We present a SAR-sensor independent method that enables assessment of image geolocation accuracy at nearly any terrestrial scene location. To achieve this, a collected image is co-registered against a global reference image set, such as the high-fidelity X-band RCS layer of the TanDEM-X High Resolution Elevation Data Exchange Program (TREx) data set, which has well-characterized horizontal and vertical errors. Measuring sensor geolocation accuracy against a high-fidelity broad-area reference set can mitigate the effect of location errors that, if left uncorrected, may have a deleterious impact on downstream applications. In particular, the proposed method could help automate the assessment and quality control of existing and emerging constellations of commercial satellite systems. Our co-registration approach first applies a pre-warp operation that exhausts known SICD (Sensor Independent Complex Data) metadata from a collected image to get within the neighborhood of the true geolocation in the reference image. Then we attain a fine scale registration through local feature detection and extraction, via an established computer vision algorithm. Finally, we compute a similarity transformation on matching points between the test and reference images; the transformation includes translation values, which are used for assessing geolocation accuracy, as well as scale and rotation estimates that are used for a confidence measure.

A single Synthetic Aperture Radar (SAR) image is a 2-Dimensional projection of a 3-Dimensional scene, with very limited ability to estimate surface topography. However, with multiple SAR images collected from suitably different geometries, they may be compared with multilateration calculations to estimate characteristics of the missing dimension. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and can be cast as a least-squares exercise. A measure of Dilution of Precision (DOP) can be used to compare the relative merits of various collection geometries.

Fast developing sub-millimeter wavelength technologies sparked off interest of the microwave community to the applicability of the optical methods for sub-millimeter system design, specifically, for aberration minimization. Both, either sphere in optics, or parabola in microwaves, need aberration correction to get the high-quality imaging in the wide-angle scanning mode. I the prototype for modification according to the results of our modeling, horizontal direction of scanning is used. Linear detector arrays is vertically oriented and configured in three columns to triple the vertical detector density for higher spatial resolution. Using the ray tracing technique, we modeled the minimization of aberrations within the whole scanning span by designing the free-form surfaces of antennas up to 7-th order of Zernike polynomials. We modeled the wavefront correction by changing the profile of mirror surfaces of antenna reflectors.