This PDF file contains the front matter associated with SPIE Proceedings Volume 9461, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

Centering the phase-center of an antenna onto the rotational axis used to measure its radiation pattern is an iterative and time consuming process. To facilitate this process, an algorithm has been developed to calculate the phase-center offset from the axis of rotation of a 2D antenna pattern. The hybrid algorithm is comprised of a combination of the two-point method to calculate the offset along the antenna mainbeam, and an antisymmetry method is used to calculate offset perpendicular to the mainbeam direction. The algorithm is tested on the E-plane radiation pattern of a cylindrical horn antenna calculated using the HFSS electromagnetic simulation engine, radiating at 5GHz. The algorithm calculates the phase-center offset to within 15%. Because the algorithm analyzes the unwrapped phase of the radiation pattern, which it converts to offset distance, no ambiguity due to offsets greater than a wavelength exist. Using this algorithm, the phase-center of the antenna can be placed coincident to the axis of rotation after the first antenna pattern is measured and analyzed.

Carbon fiber composite (CFC) materials have been used for many structural applications for decades. Their electromagnetic properties are also of great interest and are being quantified by recent research. This research explores shielding effectiveness, antenna design, conductivity, reflection, and absorption properties. The work in this paper specifically characterizes the radar cross section (RCS) of CFC structures. Various CFC planar samples were created using a wet layup method and vacuum bagging techniques. These samples were then placed in an anechoic chamber and their RCS values were measured at normal incidence. These measured values were compared to those of aluminum samples made into the same shape as the CFC samples. All of the measurements were made over 7 - 12 GHz frequency range. The RCS of the CFC samples show some interesting results. The fiber direction in the CFC samples had great influence on the RCS. Theories and reasoning for the results are presented and discussed.

The design considerations for low cost, shock resistant, compact and efficient laser radars and ranging systems are discussed. The reviewed approach with single optical aperture allows reducing the size, weight and power of the system. Additional design benefits include improved stability, reliability and rigidity of the overall system. The proposed modular architecture provides simplified way of varying the performance parameters of the range finder product family by selecting the sets of specific illumination and detection modules. The performance operation challenges are presented. The implementation of non-reciprocal optical elements is considered. The cross talk between illumination and detection channels for single aperture design is reviewed. 3D imaging capability for the ranging applications is considered. The simplified assembly and testing process for single aperture range finders that allows to mass produce the design are discussed. The eye safety of the range finder operation is summarized.

New radar applications need to perform complex algorithms and process large quantity of data to generate useful information for the users. This situation has motivated the search for better processing solutions that include low power high-performance processors, efficient algorithms, and high-speed interfaces. In this work, hardware implementation of adaptive pulse compression for real-time transceiver optimization are presented, they are based on a System-on-Chip architecture for Xilinx devices. This study also evaluates the performance of dedicated coprocessor as hardware accelerator units to speed up and improve the computation of computing-intensive tasks such matrix multiplication and matrix inversion which are essential units to solve the covariance matrix. The tradeoffs between latency and hardware utilization are also presented. Moreover, the system architecture takes advantage of the embedded processor, which is interconnected with the logic resources through the high performance AXI buses, to perform floating-point operations, control the processing blocks, and communicate with external PC through a customized software interface. The overall system functionality is demonstrated and tested for real-time operations using a Ku-band tested together with a low-cost channel emulator for different types of waveforms.

Super-computing based on Graphic Processing Unit (GPU) has become a booming field both in research and industry. In this paper, GPU is applied as the main computing device on traditional RADAR super resolution algorithms. Comparison is provided between GPU and CPU as computing architecture and MATLAB, as a widely used scientific implementation, is also included as well as C++ implementation in demonstrations of CPU part in the comparison. Fundamental RADAR algorithms as matched filter and least square estimation (LSE) are used as standard procedure to measure the efficiency of each implementation. Based on the result in this paper, GPU shows an enormous potential to expedite the traditional process of RADAR super-resolution applications.

Radio-frequency (RF) electronic targets, such as man-portable electronics, cannot be detected by traditional linear radar because the radar cross section of those targets is much smaller than that of nearby clutter. One technology that is capable of separating RF electronic targets from naturally-occurring clutter is nonlinear radar. Presented in this paper is the evolution of nonlinear radar at the United States Army Research Laboratory (ARL) and recent results of short-range over-the-air harmonic radar tests there. For the present implementation of ARL’s nonlinear radar, the transmit waveform is a chirp which sweeps one frequency at constant amplitude over an ultra-wide bandwidth (UWB). The receiver captures a single harmonic of this entire chirp. From the UWB received harmonic, a nonlinear frequency response of the radar environment is constructed. An inverse Fourier Transform of this nonlinear frequency response reveals the range to the nonlinear target within the environment. The chirped harmonic radar concept is validated experimentally using a wideband horn antenna and commercial off-the-shelf electronic targets.

This paper presents synthetic aperture radar (SAR) images of linear and nonlinear targets. Data are collected using a linear/nonlinear step frequency radar. We show that it is indeed possible to produce SAR images using a nonlinear radar. Furthermore, it is shown that the nonlinear radar is able to reduce linear clutter by at least 80 dB compared to a linear radar. The nonlinear SAR images also show the system’s ability to detect small electronic devices in the presence of large linear clutter. The system presented here has the ability to completely ignore a 20-inch trihedral corner reflector while detecting a RF mixer with a dipole antenna attached.

In a harmonic radar system design, one of the most important components is the filter used to remove the self-generated harmonics by the high-power transmitter power amplifier, which is usually driven close to its 1-dB compression point. The obvious choice for this filter is a low-pass filter. The low-pass filter will be required to attenuate stop band frequencies with 100 dB attenuation or more. Due to the high degree of attenuation required, multiple low-pass filter will likely be required. Most commercially available low-pass filters are reflective devices, which operate by reflecting the unwanted high frequencies. Cascading these reflective filter causes issues in attenuating stop band frequencies. We show that frequency diplexers are more attractive in place of reflective low-pass filters as they are able to terminate the stop band frequencies as opposed to reflecting them.

The U.S. Army Research Laboratory is studying the feasibility of using stepped-frequency, ultra-wideband (UWB) synthetic aperture radar (SAR) for the detection of nonlinear targets with harmonic frequency responses. The approach would filter out all natural clutter and manmade objects in the scene that do not have responses in the harmonic frequency bands. In this paper, we show the formulation of SAR imaging using harmonic responses from nonlinear targets. We also show the degradation in SAR image quality when the radar operates in a restricted and congested frequency spectrum where a significant percentage of the spectrum is either reserved or used by other systems. Fortunately, due to the sparse nature of the nonlinear objects in a typical scene, information in the missing frequency bands can be recovered to reduce the artifacts in SAR imagery. In this paper, we apply our sparse recovery technique to estimate the information in the missing frequency bands. Recovery performance in both raw data and SAR image domain is demonstrated using simulation and measured data from experiment.

Localization of a wireless capsule endoscope finds many clinical applications from diagnostics to therapy. There are potentially two approaches of the electromagnetic waves based localization: a) signal propagation model based localization using a priori information about the persons dielectric channels, and b) recently developed microwave imaging based localization without using any a priori information about the persons dielectric channels. In this paper, we study the second approach in terms of a variety of frequencies and signal-to-noise ratios for localization accuracy. To this end, we select a 2-D anatomically realistic numerical phantom for microwave imaging at different frequencies. The selected frequencies are 13:56 MHz, 431:5 MHz, 920 MHz, and 2380 MHz that are typically considered for medical applications. Microwave imaging of a phantom will provide us with an electromagnetic model with electrical properties (relative permittivity and conductivity) of the internal parts of the body and can be useful as a foundation for localization of an in-body RF source. Low frequency imaging at 13:56 MHz provides a low resolution image with high contrast in the dielectric properties. However, at high frequencies, the imaging algorithm is able to image only the outer boundaries of the tissues due to low penetration depth as higher frequency means higher attenuation. Furthermore, recently developed localization method based on microwave imaging is used for estimating the localization accuracy at different frequencies and signal-to-noise ratios. Statistical evaluation of the localization error is performed using the cumulative distribution function (CDF). Based on our results, we conclude that the localization accuracy is minimally affected by the frequency or the noise. However, the choice of the frequency will become critical if the purpose of the method is to image the internal parts of the body for tumor and/or cancer detection.

Current techniques for building detection in Synthetic Aperture Radar (SAR) imagery can be computationally expensive and/or enforce stringent requirements for data acquisition. We present a technique that is effective and efficient at determining an approximate building location from multi-pass single-pol SAR imagery. This approximate location provides focus-of-attention to specific image regions for subsequent processing. The proposed technique assumes that for the desired image, a preprocessing algorithm has detected and labeled bright lines and shadows. Because we observe that buildings produce bright lines and shadows with predetermined relationships, our algorithm uses a graph clustering technique to find groups of bright lines and shadows that create a building. The nodes of the graph represent bright line and shadow regions, while the arcs represent the relationships between the bright lines and shadow. Constraints based on angle of depression and the relationship between connected bright lines and shadows are applied to remove unrelated arcs. Once the related bright lines and shadows are grouped, their locations are combined to provide an approximate building location. Experimental results are presented to demonstrate the outcome of this technique.

Bistatic and multistatic antenna systems have become increasingly popular for through-wall radar imaging because of their ability to collect more target scattering information. This increased information allows for better identification of human targets in complex clutter environments. To directly compare the abilities of bistatic and multistatic systems over monostatic radar alone, both human and clutter target data were measured and used to create receiver operating characteristic curves. In addition, the use of cross-polarization radar to reduce clutter and multipath returns was investigated by taking human target data both through a wall and in an open environment. Comparisons of this data to co-polarization returns were used to determine its practicality.

Recent research and developments for in home radar monitoring have shown real promise of the technology in detecting normal and abnormal gross-motor activities of humans inside their residences and at private homes. Attention is now paid to challenges in system integration, operations, and installations. One important question touches on the required number of radar units for a given residence and whether eventually one radar unit per room would become the nominal approach. Towards addressing this question and assessing the effectiveness of radar unit to sense adjacent rooms and hallways of the same residence, this paper examines through-wall radar monitoring where the radar signal faces both wall attenuation and dispersion. We show that typical interior walls do not significantly alter the radar time-frequency (TF) signature of a fall, and the radar signal return is slightly weakened by wall penetration. Additionally, we show that there is a wide variation of the TF feature values associated with fall motions which confuse a classifier, trained with generic subjects, and cause it to falsely declare a different motion.

This paper investigates the application of SVM (Support Vector Machines) for the classification of stationary human targets and indoor clutter via spectral features. Applying Finite Difference Time Domain (FDTD) techniques allows us to examine the radar cross section (RCS) of humans and indoor clutter objects by utilizing different types of computer models. FDTD allows for the spectral characteristics to be acquired over a wide range of frequencies, polarizations, aspect angles, and materials. The acquired target and clutter RCS spectral characteristics are then investigated in terms of their potential for target classification using SVMs. Based upon variables such as frequency and polarization, a SVM classifier can be trained to classify unknown targets as a human or clutter. Furthermore, the application of feature selection is applied to the spectral characteristics to determine the SVM classification accuracy of a reduced dataset. Classification accuracies of nearly 90% are achieved using radial and polynomial kernels.

Stepped-Frequency Radars (SFRs) have become increasingly popular with the advent of new technologies and increasingly congested RF spectrum. SFRs have inherently high dynamic range due to their small IF bandwidths, allowing for the detection of weak target returns in the presence of clutter. The Army Research Laboratory’s (ARL) Partnership in Research Transition program has developed a preliminary SFR for imaging buried landmines and improvised explosive devices. The preliminary system utilizes two transmit antennas and four receive antennas and is meant to act as a transitional system to verify the system’s design and imaging capabilities. The SFR operates between 300 MHz and 2000 MHz, and is capable of 1-MHz step-sizes. The SFR system will eventually utilize 16-receive channels and will be mounted on ARL’s existing Forward-Looking Ground Penetrating Radar platform, as a replacement for the existing Synchronous Impulse REconstruction (SIRE) radar. An analysis of the preliminary SFRs radio frequency interference mitigation, spectral purity dynamic range, and maximum detectable range is presented here.

The FlexSAR radar system was designed to be a high quality, low-cost, flexible prototype instrument. Many radar researchers and practitioners desire the ability to efficiently prototype novel configurations. However, the cost and time required to modify existing radar systems is a challenging hurdle that can be prohibitive. The FlexSAR system couples an RF design that leverages connectorized components with digital commercial-off-the-shelf (COTS) cards. This design allows for a scalable system that supports software defined radio (SDR) capabilities. This paper focuses on the RF and digital system design, discussing the advantages and disadvantages. The FlexSAR system design objective was to support diverse configurations with minimal non-recurring engineering (NRE) costs. Multiple diverse applications are examined, demonstrating the flexible system nature. The configurations discussed utilize different system parameters (e.g., number of phase-centers, transmit configurations, etc.). The resultant products are examined, illustrating that high-quality data products are still attained.

The Army Research Laboratory has constructed an indoor, rail-mounted, synthetic aperture radar (SAR) system capable of simulating airborne data collection geometries. The collection facility includes both a “building within a building” for through-the-wall measurements and a “sand pit” for buried-target measurements. While we collect background measurements for the purpose of clutter removal, the elimination of multi-path responses due to target emplacements presents a significant problem. These multipath effects can manifest themselves as artifacts in the processed SAR imagery— artifacts that were observed in data presented at last year’s Defense, Security and Sensing Radar Sensor Technology conference. In this paper, we present the results of additional data collections and analysis performed to identify the source of observed Rail-SAR artifacts. We analyze data collected using various target-emplacement scenarios and describe the procedures developed to eliminate artifacts in future Rail-SAR experiments. We examine results obtained both with and without the new measurement procedures in place.

Various technologies were used to detect, track, and classify vessels on the Hudson River. Broadband radar was used to detect and track vessels. Visible light cameras, infrared cameras, and image processing techniques were used to detect, track, and classify vessels. Automatic Identification System (AIS) was used to track and classify vessels. The technologies, collectively referred to as the Integrated Technology System (ITS), were used in conjunction with each other to achieve synergies and to overcome individual system limitations. These limitations included a narrow field of view, false alarms, and misdetections. The suite of technologies successfully fulfilled its purpose. The radar was effective despite some errors. The cameras allowed for software development including automatic slewing and image processing. While AIS was considered the most reliable tool, it was determined not to be infallible. Future work includes integration of passive acoustics into the system and wake analysis for vessel detection.

A radome, or radar dome, protects a radar system from exposure to the elements. Unfortunately, radomes can affect the radiation pattern of the enclosed antenna. The co-design of a platform’s radome and radar is ideal to mitigate any deleterious effects of the radome. However, maintaining structural integrity and other platform flight requirements, particularly when integrating a new radar onto an existing platform, often limits radome electrical design choices. Radars that rely heavily on phase measurements such as monopulse, interferometric, or coherent change detection (CCD) systems require particular attention be paid to components, such as the radome, that might introduce loss and phase variations as a function of the antenna scan angle. Material properties, radome wall construction, overall dimensions, and shape characteristics of a radome can impact insertion loss and phase delay, antenna beamwidth and sidelobe level, polarization, and ultimately the impulse response of the radar, among other things, over the desired radar operating parameters. The precision-guided munitions literature has analyzed radome effects on monopulse systems for well over half a century. However, to the best of our knowledge, radome-induced errors on CCD performance have not been described. The impact of radome material and wall construction, shape, dimensions, and antenna characteristics on CCD is examined herein for select radar and radome examples using electromagnetic simulations.

A fundamental assumption when applying Synthetic Aperture Radar (SAR) to a ground scene is that all targets are motionless. If a target is not stationary, but instead vibrating in the scene, it will introduce a non-stationary phase modulation, termed the micro-Doppler effect, into the returned SAR signals. Previously, the authors proposed a pseudosubspace method, a modification to the Discrete Fractional Fourier Transform (DFRFT), which demonstrated success for estimating the instantaneous accelerations of vibrating objects. However, this method may not yield reliable results when clutter in the SAR image is strong. Simulations and experimental results have shown that the DFRFT method can yield reliable results when the signal-to-clutter ratio (SCR) > 8 dB. Here, we provide the capability to determine a target's frequency and amplitude in a low SCR environment by presenting two methods that can perform vibration estimations when SCR < 3 dB. The first method is a variation and continuation of the subspace approach proposed previously in conjunction with the DFRFT. In the second method, we employ the dual-beam SAR collection architecture combined with the extended Kalman filter (EKF) to extract information from the returned SAR signals about the vibrating target. We also show the potential for extending this SAR-based capability to remotely detect and classify objects housed inside buildings or other cover based on knowing the location of vibrations as well as the vibration histories of the vibrating structures that house the vibrating objects.

We have developed an algorithm for segmenting fully polarimetric single look TerraSAR-X, multilook SIR-C and 7 band Landsat 5 imagery using neural nets. The algorithm uses a feedforward neural net with one hidden layer to segment different surface classes. The weights are refined through an iterative filtering process characteristic of a relaxation process. Features selected from studies of fully polarimetric complex single look TerraSAR-X data and multilook SIR-C data are used as input to the net. The seven bands from Landsat 5 data are used as input for the Landsat neural net. The Cloude-Pottier incoherent decomposition is used to investigate the physical basis of the polarimetric SAR data segmentation. The segmentation of a SIR-C ocean surface scene into four classes is presented. This segmentation algorithm could be a very useful tool for investigating complex polarimetric SAR phenomena.

The purpose of this paper is to perform an analysis of RF (Radio Frequency) communication systems in a large electromagnetic environment to identify its susceptibility to jamming systems. We propose a new method that incorporates the use of reciprocity and superposition of the far-field radiation pattern of the RF system and the far-field radiation pattern of the jammer system. By using this method we can find the susceptibility pattern of RF systems with respect to the elevation and azimuth angles. A scenario was modeled with HFSS (High Frequency Structural Simulator) where the radiation pattern of the jammer was simulated as a cylindrical horn antenna. The RF jamming entry point used was a half-wave dipole inside a cavity with apertures that approximates a land-mobile vehicle, the dipole approximates a leaky coax cable. Because of the limitation of the simulation method, electrically large electromagnetic environments cannot be quickly simulated using HFSS’s finite element method (FEM). Therefore, the combination of the transmit antenna radiation pattern (horn) superimposed onto the receive antenna pattern (dipole) was performed in MATLAB. A 2D or 3D susceptibility pattern is obtained with respect to the azimuth and elevation angles. In addition, by incorporating the jamming equation into this algorithm, the received jamming power as a function of distance at the RF receiver Pr(Φr, θr) can be calculated. The received power depends on antenna properties, propagation factor and system losses. Test cases include: a cavity with four apertures, a cavity above an infinite ground plane, and a land-mobile vehicle approximation. By using the proposed algorithm a susceptibility analysis of RF systems in electromagnetic environments can be performed.

The conditions for orthogonality in Multiple Input Multiple Output (MIMO) radar enable a virtual array gain beneficial to beamforming on receive. However, this condition imposes a constraint on transmit beamforming for various reasons. As a result, a performance loss can be expected when compared to a traditional monostatic phased array. With this in mind, we analyze the complex scattering coefficients for a scenario in which MIMO radar beamforming is used to illuminate an arbitrary target obfuscated by different line-of-sight obstructions such as foliage and/or buildings. Using finite-difference time-domain (FDTD) modeling, our simulations will grow the understanding of how plausible MIMO radar is for detecting targets in challenging environments.

RF tomography has great potential in defense and homeland security applications. A distributed sensing research facility is under development at Air Force Research Lab. To develop a RF tomographic imaging system for the facility, preliminary experiments have been performed in an indoor range with 12 radar sensors distributed on a circle of 3m radius. Ultra-wideband pulses are used to illuminate single and multiple metallic targets. The echoes received by distributed sensors were processed and combined for tomography reconstruction. Traditional matched filter algorithm and truncated singular value decomposition (SVD) algorithm are compared in terms of their complexity, accuracy, and suitability for distributed processing. A new algorithm is proposed for shape reconstruction, which jointly estimates the object boundary and scatter points on the waveform’s propagation path. The results show that the new algorithm allows accurate reconstruction of object shape, which is not available through the matched filter and truncated SVD algorithms.

Interference and interference mitigation techniques degrade synthetic aperture radar (SAR) coherent data products. Radars utilizing stretch processing present a unique challenge for many mitigation techniques because the interference signal itself is modified through stretch processing from its original signal characteristics. Many sources of interference, including constant tones, are only present within the fast-time sample data for a limited number of samples, depending on the radar and interference bandwidth. Adaptive filtering algorithms to estimate and remove the interference signal that rely upon assuming stationary interference signal characteristics can be ineffective. An effective mitigation method, called notching, forces the value of the data samples containing interference to zero. However, as the number of data samples set to zero increases, image distortion and loss of resolution degrade both the image product and any second order image products. Techniques to repair image distortions,¹ are effective for point-like targets. However, these techniques are not designed to model and repair distortions in SAR image terrain. Good terrain coherence is important for SAR second order image products because terrain occupies the majority of many scenes. For the case of coherent change detection it is the terrain coherence itself that determines the quality of the change detection image. This paper proposes an unique equalization technique that improves coherence over existing notching techniques. First, the proposed algorithm limits mitigation to only the samples containing interference, unlike adaptive filtering algorithms, so the remaining samples are not modified. Additionally, the mitigation adapts to changing interference power such that the resulting correction equalizes the power across the data samples. The result is reduced distortion and improved coherence for the terrain. SAR data demonstrates improved coherence from the proposed equalization correction over existing notching methods for chirped interference sources.

A noise radar system is proposed with capabilities to measure and acquire the radar cross-section (RCS) of targets. The proposed system can cover a noise bandwidth of near DC to 50 GHz. The noise radar RCS measurements were conducted for selective targets like spheres and carpenter squares with and without dielectric bodies for a noise band of 400MHz-5000MHz. The bandwidth of operation was limited by the multiplier and the antennae used.

In this paper, the principle, simulation, and experiment results of tomographic imaging of a cylindrical conducting object using random noise waveforms are presented. Theoretical analysis of scattering and the image reconstruction technique are developed based on physical optics approximation and Fourier diffraction tomography, respectively. The bistatic radar system is designed to transmit band-limited ultra-wideband (UWB) random noise waveforms at a fixed position, and a linear scanner allows a single receiving antenna to move along a horizontal axis for backward scattering measurement in the frequency range from 3–5 GHz. The reconstructed tomographic image of the rotating cylindrical conducting object based on experimental results are seen to be in good agreement with the simulation results, which demonstrates the capability of UWB noise radar for complete two-dimensional tomographic image reconstruction of a cylindrical conducting object.

A hardware system has been developed to perform ultrawideband (UWB) noise radar tomography over the 3–5 GHz frequency range. The system utilizes RF hardware to transmit multiple independent and identically distributed UWB random noise waveforms. A 3–5 GHz band-limited signal is generated using an arbitrary waveform generator and the waveform is then amplified and transmitted through a horn antenna. A linear scanner with a single antenna is used in place of an antenna array to collect backscatter. The backscatter is collected from the transmission of each waveform and reconstructed to form an image. The images that result from each scan are averaged to produce a single tomographic image of the target. After background subtraction, the scans are averaged to improve the image quality. The experimental results are compared to the theoretical predictions. The system is able to successfully image metallic and dielectric cylinders of different cross sections.

In order to achieve low probability-of-intercept (LPI), radar waveforms are usually long and randomly generated. Due to the randomized nature, Matched filter responses (autocorrelation) of those waveforms can have high sidelobes which would mask weaker targets near a strong target, limiting radar’s ability to distinguish close-by targets. To improve resolution and reduced sidelobe contaminations, a waveform independent pulse compression filter is desired. Furthermore, the pulse compression filter needs to be able to adapt to received signal to achieve optimized performance. As many existing pulse techniques require intensive computation, real-time implementation is infeasible. This paper introduces a new adaptive pulse compression technique for LPI waveforms that is based on a nonparametric iterative adaptive approach (IAA). Due to the nonparametric nature, no parameter tuning is required for different waveforms. IAA can achieve super-resolution and sidelobe suppression in both range and Doppler domains. Also it can be extended to directly handle the matched filter (MF) output (called MF-IAA), which further reduces the computational load. The practical impact of LPI waveform operations on IAA and MF-IAA has not been carefully studied in previous work. Herein the typical LPI waveforms such as random phase coding and other non- PI waveforms are tested with both single-pulse and multi-pulse IAA processing. A realistic airborne radar simulator as well as actual measured radar data are used for the validations. It is validated that in spite of noticeable difference with different test waveforms, the IAA algorithms and its improvement can effectively achieve range-Doppler super-resolution in realistic data.

We present an analysis of receiver performance when diverse waveforms such as the advanced pulse compression noise (APCN) are used. Two perspectives within the shared channel are considered: (1) a radar transceiving APCN in the presence of other radar interference sources, and (2) a communications system transceiving M-ary quadrature amplitude modulation (QAM) in the presence of a radar interference sources practicing waveform diversity. Through simulation, we show how waveform diversity and the ability to tune the APCN spectrum characteristics minimizes interference for co-channel users.

We propose a scheme for bistatic radar that uses a chaotic system to generate a wideband FM signal that is reconstructed at the receiver via a conventional phase lock loop. The setup for the bistatic radar includes a 3 state variable drive oscillator at the transmitter and a response oscillator at the receiver. The challenge is in synchronizing the response oscillator of the radar receiver utilizing a scaled version of the transmitted signal s_r(t, x) = αs_t(t, x) where x is one of three driver oscillator state variables and α is the scaling factor that accounts for antenna gain, system losses, and space propagation. For FM, we also assume that the instantaneous frequency of the received signal, x_s, is a scaled version of the Lorenz variable x. Since this additional scaling factor may not be known a priori, the response oscillator must be able to accept the scaled version of x as an input. Thus, to achieve synchronization we utilize a generalized projective synchronization technique that introduces a controller term –μe where μ is a control factor and e is the difference between the response state variable x_s and a scaled x. Since demodulation of s_r(t) is required to reconstruct the chaotic state variable x, the phase lock loop imposes a limit on the minimum error e. We verify through simulations that, once synchronization is achieved, the short-time correlation of x and x_s is high and that the self-noise in the correlation is negligible over long periods of time.

Most of the advances in current radar systems are aimed at improving their resolution. As a result, their operating frequency has been increased from 10GHz up to 94GHz, and new millimeter-wave (100-300GHz) radar systems are currently being studied. One of the major concerns with these frequencies is the associated large bandwidth requirement. Compressive Sensing (CS), also known as Compressive Sampling, has been proposed as a solution to overcome the aforementioned problems by exploiting the sparsity of the radar signal. Using the CS method, a sparse signal can be reconstructed even if it is sampled below the Nyquist rate. This method provides a completely new way to reconstruct the signal using optimization techniques and a minimum number of observations. The objective of this research project is to investigate and develop a Chaotic Radar Imaging system that leverages Compressive Sensing (CS) technology to improve the image resolution without increasing the amount of processed data. In addition to demonstrating the validity of the proposed approach through simulations, this project seeks to develop and implement hardware prototypes for the proposed imaging radar system. Simulated chaotic radar data was generated and loaded to the FPGA board to test the algorithms and their performance. The results from implementing the Orthogonal Matching Pursuit (OMP), the Compressive Sensing Matching Pursuit (CSMP), and the Stagewise Orthogonal Matching Pursuit (StOMP) algorithms to a Xilinx ZedBoard will be presented.

Quantum radar is an emerging field that shows a lot of promise in providing significantly improved resolution compared to its classical radar counterpart. The key to this kind of resolution lies in the correlations created from the entanglement of the photons being used. Currently, the technology available only supports quantum radar implementation and validation in the optical regime, as opposed to the microwave regime, because microwave photons have very low energy compared to optical photons. Furthermore, there currently do not exist practical single photon detectors and generators in the microwave spectrum. Viable applications in the optical regime include deep sea target detection and high resolution detection in space. In this paper, we propose a conceptual architecture of a quantum radar which uses entangled optical photons based on Spontaneous Parametric Down Conversion (SPDC) methods. After the entangled photons are created and emerge from the crystal, the idler photon is detected very shortly thereafter. At the same time, the signal photon is sent out towards the target and upon its reflection will impinge on the detector of the radar. From these two measurements, correlation data processing is done to obtain the distance of the target away from the radar. Various simulations are then shown to display the resolution that is possible.

Sidelobe structures on classical radar cross section graphs are a consequence of discontinuities in the surface currents. In contrast, quantum radar theory states that sidelobe structures on quantum radar cross section graphs are due to quantum interference. Moreover, it is conjectured that quantum sidelobe structures may be used to detect targets oriented off the specular direction. Because of the high data bandwidth expected from quantum radar, it may be necessary to use sophisticated quantum signal analysis algorithms to determine the presence of stealth targets through the sidelobe structures. In this paper we introduce three potential quantum algorithmic techniques to compute classical and quantum radar cross sections. It is our purpose to develop a computer science-oriented tool for further physical analysis of quantum radar models as well as applications of quantum radar technology in various fields.

One of the major scientific thrusts from recent years has been to try to harness quantum phenomena to dramatically increase the performance of a wide variety of classical information processing devices. These advances in quantum information science have had a considerable impact on the development of standoff sensors such as quantum radar. In this paper we analyze the theoretical performance of low-brightness quantum radar that uses entangled photon states. We use the detection error probability as a measure of sensing performance and the interception error probability as a measure of stealthiness. We compare the performance of quantum radar against a coherent light sensor (such as lidar) and classical radar. In particular, we restrict our analysis to the performance of low-brightness standoff sensors operating in a noisy environment. We show that, compared to the two classical standoff sensing devices, quantum radar is stealthier, more resilient to jamming, and more accurate for the detection of low reflectivity targets.

There are an infinite number of ways to represent a classical bit with a quantum state. By taking advantage of this fact, one can develop methods for reducing error rates in computation, communication and sensing that do not require the use of quantum codes. But how well do they work? In this paper, we give results that can be used to quantify the improvement offered by such methods.

Correlations between entangled quantum states can be exploited to dramatically improve detection sensitivity under certain conditions. In this paper we argue that space-based surveillance ideally satisfies these conditions and represents a practical application of quantum sensing for the detection of near-earth objects which threaten spacecraft or terrestrial life.

Localization of a wireless capsule endoscope finds many clinical applications from diagnostics to therapy. There are potentially two approaches of the electromagnetic waves based localization: a) signal propagation model based localization using a priori information about the persons dielectric channels, and b) recently developed microwave imaging based localization without using any a priori information about the persons dielectric channels. In this paper, we study the second approach in terms of a variety of frequencies and signal-to-noise ratios for localization accuracy. To this end, we select a 2-D anatomically realistic numerical phantom for microwave imaging at different frequencies. The selected frequencies are 13:56 MHz, 431:5 MHz, 920 MHz, and 2380 MHz that are typically considered for medical applications. Microwave imaging of a phantom will provide us with an electromagnetic model with electrical properties (relative permittivity and conductivity) of the internal parts of the body and can be useful as a foundation for localization of an in-body RF source. Low frequency imaging at 13:56 MHz provides a low resolution image with high contrast in the dielectric properties. However, at high frequencies, the imaging algorithm is able to image only the outer boundaries of the tissues due to low penetration depth as higher frequency means higher attenuation. Furthermore, recently developed localization method based on microwave imaging is used for estimating the localization accuracy at different frequencies and signal-to-noise ratios. Statistical evaluation of the localization error is performed using the cumulative distribution function (CDF). Based on our results, we conclude that the localization accuracy is minimally affected by the frequency or the noise. However, the choice of the frequency will become critical if the purpose of the method is to image the internal parts of the body for tumor and/or cancer detection.

This paper presents our work on the reconstruction of the complex permittivity 2-D profile of biological objects simulated as circular phantoms. An iterative reconstruction algorithm called the Levenberg-Marquardt method developed by Franchois and Pichot is tested using synthetic data. Assumed permittivity profiles are generated for a simple circular phantom using the CST microwave studio software. Then, we reconstruct the permittivity profile of the object in MATLAB by using the data from CST microwave studio. The main work in this paper focuses on the realization of the inversion algorithm on three different circular phantoms. Our results show that the permittivity profiles can be very satisfactorily reconstructed, thereby indicating the usefulness of this approach for medical diagnosis.

Human intestines are vital organs, which are often subjected to chronic issues. In particular, Crohn's disease is a bowel aliment resulting in inflammation along the lining of one's digestive tract. Moreover, such an inflammatory condition causes changes in the thickness of the intestines; and we posit induce changes in the dielectric properties detectable by radar. This detection hinges on the increase in fluid content in the afflicted area, which is described by effective medium approximations (EMA). In this paper, we consider one of the constitutive parameters (i.e. relative permittivity) of different human tissues and introduce a simple numerical, electromagnetic multilayer model. We observe how the increase in water content in one layer can be approximated to predict the effective permittivity of that layer. Moreover, we note trends in how such an accumulation can influence the total effective reflection coefficient of the multiple layers.

Human heartbeats and respiration can be detected from a distance using radar. This can be used for medical applications and human being detection. It is useful to have a system independent measure of how detectable the vital signs are. In radar applications, the Radar Cross Section (RCS) is normally used to characterize the detectability of an object. Since the human vital signs are seen by the radar as movements of the torso, the modulations in the person RCS can be used as a system independent measure of the vital signs detectability. In this paper, measurements of persons seated in an anechoic chamber are presented. The measurements were calibrated using empty room and a metallic calibration sphere. A narrowband radar operating at frequencies from 500 MHz to 18 GHz in discrete steps was used. A turntable provided measurements at precise aspect angles all around the person under test. In an I & Q receiver, the heartbeat and respiration modulation is a combination of amplitude and phase mod- modulations. The measurements were filtered, leaving the modulations from the vital signs in the radar recordings. The procedure for RCS computation was applied to these filtered data, capturing the complex signatures. It was found that both the heartbeat and respiration detectability increase with increasing frequency. The heartbeat signatures are almost equal from the front and the back, while being almost undetectable from the sides of the person. The respiration signatures are slightly higher from the front than from the back, and smaller from the sides. The signature measurements presented in this paper provide an objective system independent measure of the detectability of human vital signs as a function of frequency and aspect angle. These measures are useful for example in system design and in assessing real measurement scenarios.

In this paper, we analyze the micro-Doppler signatures of elderly gait patterns in the presence of walking aids using radars. The signatures are based on real data experiments conducted in a laboratory environment using human subjects walking with a walking cane and a walker. Short-time Fourier transform is used to provide the local signal behavior over frequency and to detail the changes in the micro-Doppler signatures over time. Intrinsic differences in the Doppler and micro-Doppler signatures of the elderly gait observed with and without the use of a walking aid are highlighted. Features that capture these differences can be effective in discriminating gait with walking aids from normal human gait.

In this paper, we examine the role of high-resolution time-frequency distributions (TFDs) of radar micro-Doppler signatures for fall detection. The work supports the recent and rising interest in using emerging radar technology for elderly care and assisted living. Spectrograms have been the de facto joint-variable signal representation, depicting the signal power in both time and frequency. Although there have been major advances in designing quadratic TFDs which are superior to spectrograms in terms of detailing the local signal behavior, the contributions of these distributions in the area of human motion classifications and their offerings in enhanced feature extractions have not yet been properly evaluated. The main purpose of this paper is to show the effect of using high-resolution TFD kernels, in lieu of spectrogram, on fall detection. We focus on the extended modified B-distribution (EMBD) and exploit the level of details it provides as compared with the coarse and smoothed time-frequency signatures offered by spectrograms.

In the past few decades, there were many imaging algorithms designed in the case of the absence of multiple scattering. Recently, we discussed an algorithm for removing high order scattering components from collected data. This paper is a continuation of our previous work. First, we investigate the current state of multiple scattering in SAR. Then, we revise our method and test it. Given an estimate of our target reflectivity, we compute the multi scattering effects in the target region for various frequencies. Furthermore, we propagate this energy through free space towards our antenna, and remove it from the collected data.

Publisher’s Note: This paper, originally published on 21 May 2015, was replaced with a corrected/revised version on 2 September, 2015 (corrected data in tables 3 and 4). If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. This paper presents the results of our experimental investigation into the radar micro-Doppler signatures (MDS) of various human activities both in free-space and through-wall environments. The collection of MDS signatures was divided into two categories: stationary and forward-moving. Each category of MDS signatures encompassed a variety of movements associated with it, adding up to a total of 14 human movements. Using a 6.5-GHz C-band coherent radar, the MDS of six human subjects were gathered in free-space and through-wall environments. The MDS for these cases were analyzed in detail and the general properties of the signatures were related to their associated phenomenological characteristics. Based upon the MDS, specific features for designing detectors and classifiers of human targets performing such movements are extracted.

The successful implementation of autonomous driving in an urban setting depends on the ability of the environment perception system to correctly classify vulnerable road users such as pedestrians and bicyclists in dense, complex scenarios. Self-driving vehicles include sensor systems such as cameras, lidars, and radars to enable decision making. Among these systems, radars are particularly relevant due to their operational robustness under adverse weather and night light conditions. Classification of pedestrian and car in urban settings using automotive radar has been widely investigated, suggesting that micro-Doppler signatures are useful for target discrimination. Our objective is to analyze and study the micro-Doppler signature of bicyclists approaching a vehicle from different directions in order to establish the basis of a classification criterion to distinguish bicycles from other targets including clutter. The micro-Doppler signature is obtained by grouping individual reflecting points using a clustering algorithm and observing the evolution of all the points belonging to an object in the Doppler domain over time. A comparison is then made with simulated data that uses a kinematic model of bicyclists’ movement. The suitability of the micro-Doppler bicyclist signature as a classification feature is determined by comparing it to those belonging to cars and pedestrians approaching the automotive radar system.

Ladar and other 3D imaging modalities have the capability of creating 3D micro-Doppler to analyze the micro-motions of human subjects. An additional capability to the recognition of micro-motion is the recognition of the moving part, such as the hand or arm. Combined with measured RCS values of the body, ladar imaging can be used to ground-truth the more sensitive radar micro-Doppler measurements and associate the moving part of the subject with the measured Doppler and RCS from the radar system. The 3D ladar signatures can also be used to classify activities and actions on their own, achieving an 86% accuracy using a micro-Doppler based classification strategy.

This paper addresses use of the micro-Doppler effect and the use of high range-resolution profiles to observe complex targets in complex target scenes. The combination of micro-Doppler and high range-resolution provides the ability to separate the motion of complex targets from one another. This ability leads to the differentiation of targets based on their micro-Doppler signatures. Without the high-range resolution, this would not be possible because the individual signatures would not be separable. This paper also addresses the use of the micro-Doppler information and high range-resolution profiles to generate an approximation of the scattering properties of a complex target. This approximation gives insight into the structure of the complex target and, critically, is created without using a pre-determined target model.

There is much interest in detecting a target and optical communications from an airborne platform to a platform submerged under water. Accurate detection and communications between underwater and aerial platforms would increase the capabilities of surface, subsurface, and air, manned and unmanned vehicles engaged in oversea and undersea activities. The technique introduced in this paper involves a Laser Doppler Vibrometer (LDV) for acousto-optic sensing for detecting acoustic information propagated towards the water surface from a submerged platform inside a 12 gallon water tank. The LDV probes and penetrates the water surface from an aerial platform to detect air-water surface interface vibrations caused by an amplifier to a speaker generating a signal generated from underneath the water surface (varied water depth from 1” to 8”), ranging between 50Hz to 5kHz. As a comparison tool, a hydrophone was used simultaneously inside the water tank for recording the acoustic signature of the signal generated between 50Hz to 5kHz. For a signal generated by a submerged platform, the LDV can detect the signal. The LDV detects the signal via surface perturbations caused by the impinging acoustic pressure field; proving a technique of transmitting/sending information/messages from a submerged platform acoustically to the surface of the water and optically receiving the information/message using the LDV, via the Doppler Effect, allowing the LDV to become a high sensitivity optical-acoustic device. The technique developed has much potential usage in commercial oceanography applications. The present work is focused on the reception of acoustic information from an object located underwater.

Publisher’s Note: This paper, originally published on 21 May 2015, was withdrawn per author request, if you have any questions please contact SPIE Digital Library Customer Service for assistance.

Soil target signatures vary due to geometry, chemical composition, and scene radiometry. Although radiative transfer models and function-fit physical models may describe certain targets in limited depth, the ability to incorporate all three signature variables is difficult. This work describes a method to simulate the transient signatures of soil by first considering scene geometry synthetically created using 3D physics engines. Through the assignment of spectral data from the Nonconventional Exploitation Factors Data System (NEFDS), the synthetic scene is represented as a physical mixture of particles. Finally, first principles radiometry is modeled using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. With DIRSIG, radiometric and sensing conditions were systematically manipulated to produce and record goniometric signatures. The implementation of this virtual goniometer allows users to examine how a target bidirectional reflectance distribution function (BRDF) will change with geometry, composition, and illumination direction. By using 3D computer graphics models, this process does not require geometric assumptions that are native to many radiative transfer models. It delivers a discrete method to circumnavigate the significant cost of time and treasure associated with hardware-based goniometric data collections.

A good measure for the probability to detect a sniper telescopic sight is the effective bi-directional laser retro-reflection cross section. This angular (bi-directional) property of an optical device can be measured and can be used for a fist estimation of its probability to be detected by an active imaging. In the present paper, the authors give examples for resolved and non-resolved sensing of a telescopic sight under mono-static and bi-static conditions. As a result of these measurements, the resolved sensing under mono-static conditions shows the highest signal response in a wide angular range.

Knowledge of the spectral reflectance signature of human skin over a wide spectral range will help advance the development of sensing systems for many applications, ranging from medical treatment to security technology. A critical component of the signature of human skin is the variability across the population. We describe a simple measurement method to measure human skin reflectance of the inside of the forearm. The variability of the reflectance spectra for a number of subjects measured at NIST is determined using statistical methods. The degree of variability is explored and discussed. We also propose a method for collaborating with other scientists, outside of NIST, to expand the data set of signatures to include a more diverse population and perform a meta-analysis to further investigate the variability of human skin reflectance.

There is a need for stable test standards for many remote sensing applications that can be used both in the laboratory and in rugged test environments. Ideally these standards would be stable over time such that the same standard could be used from year to year for comparison of system performance. While ink-jet and spray gun methods can disperse controlled doses of dissolved analytes, methods to maintain particle size spectral variations are lacking. In addition, standards that are environmentally robust and stable over time are limited. As part of the recent Lighthouse work toward a Hyperspectral Imagery (HSI) proximal handheld sensor, Special Technologies Laboratory (STL) was tasked to do preliminary work toward a rugged, transportable, waterproof target board. This involved developing test standards using minerals of known particle sizes that have spectrally relevant features. Mineral powders were dispersed in binders that did not change their spectral characteristics. These standards were packaged such that they could be transported and used repeatedly. This paper discusses the methodology for developing this preliminary set of targets. Target sizes were limited to the proximal case, and further work is required to finalize the optimum binder and examine other possible appropriate minerals.

Nowadays polarimetric decompositions are common processing techniques for synthetic aperture radar images. However, some of the decomposition methods can also be applied to imagery obtained in radar cross-section measurement ranges. Since commonly artificial targets are measured in these ranges, coherent decompositions are of special interest for the analysis of these images. In this paper, a Kennaugh matrix decomposition is used to remove non-polarized clutter from fully polarized targets. Therefore two averaging techniques required for the decomposition will be compared. Also a variation of this decomposition which is related to a well-known image processing filter will be introduced. Finally it will be demonstrated that both methods can enhance the contrast of radar cross-section images.

We analyze an interaction of THz pulse containing a few cycles with absorbing or transparent layer. The process under consideration is described by 1D Maxwell’s equations. This analysis is very important for problem of the detection and identification of substance because at the interaction of such THz pulse with layer, the pulse spectrum can essentially change in dependence of a layer thickness. As consequence, excitation of different energy levels occurs in spite of the spectrum unchanging for the incident pulse. Therefore, the medium response can change essentially due to changing of emission frequencies. We found out the non-monotonic dependence of a reflection coefficient from both absorption coefficient, and layer thickness, and absolute phase of the pulse. For the detection and identification of substances, this dependence leads to additional requirements with respect to the incident THz pulse spectrum. For absorbing layer, we see non-monotonic dependence of absorption energy from the layer thickness and its reflection coefficient. This dependence has maximum with changing of the absorption coefficient because a reflection of laser energy is a function of both dielectric permittivity of a medium and its absorption coefficient. Amplitude of reflected THz pulse depends in strong way from the absolute phase of incident THz pulse if the pulse duration is sufficient small.

Greatly improved understanding of areas and objects of interest can be gained when real time, full-motion Flash LiDAR is fused with inertial navigation data and multi-spectral context imagery. On its own, full-motion Flash LiDAR provides the opportunity to exploit the z dimension for improved intelligence vs. 2-D full-motion video (FMV). The intelligence value of this data is enhanced when it is combined with inertial navigation data to produce an extended, georegistered data set suitable for a variety of analysis. Further, when fused with multispectral context imagery the typical point cloud now becomes a rich 3-D scene which is intuitively obvious to the user and allows rapid cognitive analysis with little or no training. Ball Aerospace has developed and demonstrated a real-time, full-motion LIDAR system that fuses context imagery (VIS to MWIR demonstrated) and inertial navigation data in real time, and can stream these information-rich geolocated/fused 3-D scenes from an airborne platform. In addition, since the higher-resolution context camera is boresighted and frame synchronized to the LiDAR camera and the LiDAR camera is an array sensor, techniques have been developed to rapidly interpolate the LIDAR pixel values creating a point cloud that has the same resolution as the context camera, effectively creating a high definition (HD) LiDAR image. This paper presents a design overview of the Ball TotalSight™ LIDAR system along with typical results over urban and rural areas collected from both rotary and fixed-wing aircraft. We conclude with a discussion of future work.

The Johns Hopkins University MultiModal Action (JHUMMA) dataset contains a set of twenty-one actions recorded with four sensor systems in three different modalities. The data was collected with a data acquisition system that includes three independent active sonar devices at three different frequencies and a Microsoft Kinect sensor that provides both RGB and Depth data. We have developed algorithms for human action recognition from active acoustics and provide benchmark baseline recognition performance results.

High-performance radar operation, particularly Ground Moving Target Indicator (GMTI) radar modes, are very sensitive to anomalous effects of system nonlinearities. System nonlinearities generate harmonic spurs that at best degrade, and at worst generate false target detections. One significant source of nonlinear behavior is the Analog to Digital Converter (ADC). One measure of its undesired nonlinearity is its Integral Nonlinearity (INL) specification. We examine in this paper the relationship of INL to radar performance; in particular its manifestation in a range-Doppler map or image.

The trend in high-performance ground-surveillance radar systems is towards employing multiple receiver channels of data. Often, key to performance is the ability to achieve and maintain balance between the radar channels. This can be quite problematic for high-performance radar modes. It is shown that commutation of radar receiver channels can be employed to facilitate channel balancing. Commutation is the switching, trading, toggling, or multiplexing of the channels between signal paths. Commutation allows modulating the imbalance energy away from the balanced energy in Doppler, where it can be mitigated with filtering.

Radar Intelligence, Surveillance, and Reconnaissance (ISR) does not always involve cooperative or even friendly environments or targets. The environment in general, and an adversary in particular, may offer numerous characteristics and impeding techniques to diminish the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the Electromagnetic (EM) signals required by the radar sensor. Consequently mitigation techniques are often prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.

Modern high-performance radar systems’ data is often rendered to distinguish between positive and negative frequencies necessitating complex data values, with real and imaginary constituents typically termed In-phase (I) and Quadrature (Q) elements respectively. Processing this data generally assumes well-balanced I/Q data, which may often be problematic due to non-ideal component and circuit behavior. We offer a number of techniques to mitigate the effects of I/Q imbalance.

Single aperture range finders with eye safe lasers due to their smaller size and simplified design have a strong potential for wide implementation in military and commercial systems. In this paper we present the results of experimental evaluation of a single aperture laser range finder. The new design operates at eye safe wavelength range around 1535 nm and uses passively Q switched laser for illumination. The optical circulator is used to separate the detection and illumination channels. The measurements of the power budget and ranging performance evaluation for the new design are discussed.

The complex coherence function describes information that is necessary to create maps from interferometric synthetic aperture radar (InSAR). This coherence function is complicated by building layover. This paper presents a mathematical model for this complex coherence in the presence of building layover and shows how it can describe intriguing phenomena observed in real interferometric SAR data.

Researchers have recently developed radar systems capable of exploiting non-linear target responses to precisely locate targets in range. These systems typically achieve the bandwidth necessary for range resolution through transmission of either a stepped-frequency or chirped waveform. The second harmonic of the reflected waveform is then analyzed to isolate the non-linear target response. In other experiments, researchers have identified certain targets through the inter-modulation products they produce in response to a multi-tone stimulus. These experiments, however, do not exploit the phase information available in the inter-modulation products. We present a method for exploiting both the magnitude and phase information available in the inter-modulation products to create an “instantaneous” stepped frequency, non-linear target response. The new approach enables us to both maintain the unambiguous range dictated by the fundamental, multi-tone separation and obtain the entire target signature from a single transmitted waveform.

We propose a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly-moving target using an orthogonal frequency division multiplexing (OFDM) radar. The motivation of employing an OFDM signal is that it improves the target-detectability from the interfering signals by increasing the frequency diversity of the system. However, due to the addition of one extra dimension in terms of frequency, the adaptive degrees-of- freedom in an OFDM-STAP also increases. Therefore, to avoid the construction a fully-adaptive OFDM-STAP, we propose a sparsity-based STAP algorithm. We observe that the interference spectrum is inherently sparse in the spatio-temporal domain, as the clutter responses occupy only a diagonal ridge on the spatio-temporal plane and the jammer signals interfere only from a few spatial directions. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data compared to the other existing STAP techniques, and produces nearly optimum STAP performance. In addition to designing the STAP filter, we propose to optimally design the transmit OFDM signals by maximizing the output signal- to-interference-plus-noise ratio (SINR) in order to improve the STAP-performance. The computation of output SINR depends on the estimated value of the interference covariance matrix, which we obtain by applying the sparse recovery algorithm. Therefore, we analytically assess the effects of the synthesized OFDM coefficients on the sparse recovery of the interference covariance matrix by computing the coherence measure of the sparse measurement matrix. Our numerical examples demonstrate the achieved STAP-performance due to sparsity- based technique and adaptive waveform design.