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Methods for addressing two types of multiplicative noise in synthetic aperture radar (SAR) imaging are presented. The authors consider a multiplicative noise with a real phase (i.e. the SAR signal's phase is contaminated but its amplitude is uncorrupted) that possesses unknown functional characteristics with respect to the radar signal's temporal frequencies. A perturbation solution for phase reconstruction from amplitude is developed from a wave equation governing the SAR signal and a Riccati equation that relates the amplitude and phase functions of the SAR signal. This solution is converted into a noniterative analytical solution in terms of the moments and powers of the log amplitude function. Next, the authors consider a multiplicative noise with a complex phase (i.e. both the amplitude and phase of the SAR signal are contaminated) that varies linearly with respect to the radar signal's temporal frequencies. The two wave equations governing the SAR signal at two temporal frequencies of the radar signal are combined to derive a method to reconstruct the complex phase error function. >

A system model and its corresponding inversion for synthetic aperture radar (SAR) imaging are presented. The system model incorporates the spherical nature of a radar's radiation pattern at far field. The inverse method based on this model performs a spatial Fourier transform (Doppler processing) on the recorded signals with respect to the available coordinates of a translational radar (SAR) or target (inverse SAR). It is shown that the transformed data provide samples of the spatial Fourier transform of the target's reflectivity function. The inverse method can be modified to incorporate deviations of the radar's motion from its prescribed straight line path. The effects of finite aperture on resolution, reconstruction, and sampling constraints for the imaging problem are discussed. >

The U.S. Department of Defense Humanitarian Demining (HD) Research and Development Program focuses on developing, testing, demonstrating, and validating new technology for immediate use in humanitarian demining operations around the globe. Beginning in the late 1990's, the U.S. Army Countermine Division funded the development of the NIITEK ground penetrating radar (GPR) for detection of anti-tank (AT) landmines. This work is concerned with signal processing algorithms to suppress sources of artifacts in the NIITEK GPR, and formation of three-dimensional (3D) imagery from the resultant data. We first show that the NIITEK GPR data correspond to a 3D Synthetic Aperture Radar (SAR) database. An adaptive filtering method is utilized to suppress ground return and self-induced resonance (SIR) signals that are generated by the interaction of the radar-carrying platform and the transmitted radar signal. We examine signal processing methods to improve the fidelity of imagery for this 3D SAR system using pre-processing methods that suppress Doppler aliasing as well as other side lobe leakage artifacts that are introduced by the radar radiation pattern. The algorithm, known as digital spotlighting, imposes a filtering scheme on the azimuth-compressed SAR data, and manipulates the resultant spectral data to achieve a higher PRF to suppress the Doppler aliasing. We also present the 3D version of the Fourier-based wavefront reconstruction, a computationally-efficient and approximation-free SAR imaging method, for image formation with the NIITEK 3D SAR database.

A synthetic aperture acoustic approach is used as a standoff method to assess material properties of a typical cinder block, referred to as a concrete masonry unit (CMU), and a variety of CMU surrogates. The objective is to identify anomalies in CMU wall surfaces. The acoustic specular return and phase change across the blocks are the fundamental measurements of interest. The CMU surrogates are created from commercially available closed cell expanding foam. Results from three test articles are presented that show potentially exploitable differences in terms of acoustic magnitude and acoustic phase response between the surrogates and typical CMUs. The test articles are; a typical CMU, a foam block, and a foam block with an embedded steel object. All test articles are similar in size and shape, and both foam blocks are covered in grout so that surface appearance closely matches that of a CMU. The results show that each of the test articles has characteristics that may be used for discrimination and anomaly detection.

This paper is concerned with imaging and moving target detection using a Synthetic Aperture Radar (SAR) platform that is known as Gotcha. The SAR platform can interrogate a scene using an imperfect circular trajectory; we refer to this as nonlinear SAR data collection. This collection can make monostatic and quasi-monostatic measurements in the along-track domain. We present subaperture-based wavefront reconstruction algorithms for motion compensation and imaging from this nonlinear SAR database. We also discuss adaptive filtering algorithms to construct MTI imagery from the two receiver channels of the system. Results will be provided.

This paper is concerned with an echo imaging system which utilizes focused beams of an aperture along a specific contour, for example, a line or a circular arc, in both the transmit and receive modes for data collection. Such data collection strategies are useful for imaging internal structures of a target which are located at a certain depth relative to the aperture; unfocused echo signature of an interior structure possesses a low signal-to-clutter/noise power ratio, and is not desirable. The conventional methods for depth-focused echo imaging use transmit/receive focusing on a set of prescribed points in the spatial domain (that is, a two-dimensional grid); this is exceedingly time-consuming though it does not require any postprocessing of the measured data. The proposed scheme of depth-focusing along a contour requires a significantly smaller time period for data acquisition, and relies on a relatively fast Fourier-based method for image formation. This Fourier-based method is shown to be applicable in near-field as well as far-field imaging scenarios, and does not put any restrictions on the size of the aperture, the size of the target area, and the frequency of radiation. The approach is applicable in depth-focused imaging with a mechanically rotating focused aperture, or a phased array. Results are provided.

Radar systems have long been recognized as an effective tool for detecting moving targets--a problem commonly referred to as moving target indication (MTI). Recent advances, including Space Time Adaptive Processing (STAP), allow for even more precise determination of a target's location relative to the radar. Still, most of these methods approach MTI from the point of view of parameter estimation, and this sort of an approach can become problematic when the target speed is low and its associated Doppler frequency is near zero. In such cases the target signature is masked by the stationary, background clutter. Another potential drawback to STAP techniques arises from the fact that they require a relatively large number of receive channels, adding additional complexity to the radar system hardware. In this paper we present a moving-target-indication (MTI) technique that is based on a change detection paradigm. That is, rather than estimating the Doppler frequency associated with a target's motion, we propose to detect subtle differences between simultaneously collected, complex SAR images. We use simulated data to illustrate the feasibility of the approach under several different operating scenarios.

Ground Penetrating Radar (GPR) has been applied for several years to the problem of detecting both antipersonnel and anti-tank landmines. RDECOM CERDEC NVESD is developing an airborne wideband GPR sensor for the detection of minefields including surface and buried mines. In this paper, we describe the as-built system, data and image processing techniques to generate imagery, and current issues with this type of radar. Further, we will display images from a recent field test.

In support of the U.S. Army vision for increased mobility, survivability, and lethality, the Army Research Laboratory is currently developing a new version of the low frequency ultra-wideband (UWB) synthetic aperture radar (SAR) to support forward imaging. One of the goals in the development of this version of the radar is to make it affordable. This paper presents a study of various forward imaging radar configurations that could be employed in a forward imaging radar system to achieve good imaging resolution with a reasonable number of transmitters/receivers. This study provided us with insights to efficiently configure our transmitter/receiver array. In this study, we examined various radar configurations such as monostatic and some variations of bistatic cases. We provide the analysis of the synthetic aperture radar (SAR) image resolution for these configurations and show the effectiveness of the bistatic configuration with only two transmitters at the ends of the physical array. In addition to the analysis, we also provide simulation results to demonstrate the expected imaging resolutions with respect to the radar configuration and the imaging geometry. Finally, we also consider the use of two squinted transmitters at the two ends and exploit the forward motion of the vehicle to form image on the two sides.

In the past, many researchers have approached the "Hyperspectral-imagery-anomaly-detection" problem from the point of view of classical detection theory. This perspective has resulted in the development of algorithms like RX (Reed-Xiaoli) and the application of processing techniques like PCA (Principal Component Analysis) and ICA (Independent Component Analysis--algorithms and techniques that are based primarily on statistical and probabilistic considerations. In this paper we describe a new anomaly detection paradigm based on an adaptive filtering strategy known as "signal subspace processing". The signal-subspace-processing (SSP) techniques on which our algorithm is based have yielded solutions to a wide range of problems in the past (e.g. sensor calibration, target detection, and change detection). These earlier applications, however, utilized SSP to relate reference and test signals that were collected at different times. For our current application, we formulate an approach that relates signals from one spatial region in a hyperspectral image to those from a nearby spatial region in the same image. The motivation and development of the technique are described in detail throughout the course of the paper. We begin by developing the signal subspace processing anomaly detector (SSPAD) and proceed to illustrate how it arises naturally from the adaptive filtering formulation. We then compare the algorithm with existing anomaly-detection schemes, noting similarities and differences. Finally, we apply both the SSPAD and various existing anomaly detectors to a hyperspectral data set and compare the results via receiver operating characteristic (ROC) curves.

The authors present a synthetic aperture radar (SAR) coherent system model and inversion (ISAR) to image a target moving with an unknown constant velocity in a stationary background. It is shown that SAR imaging of a moving target can be converted into imaging the target in a stationary squint-mode SAR problem where the parameters of the squint-mode geometry depend on the target's velocity. A method for estimating the moving target's velocity that utilizes a spatial Doppler analysis of the SAR data within overlapping subapertures is presented. On estimating a moving target's velocity, unlike the temporal Doppler processing methods, the spatial Doppler technique does not require the radar signal to be narrowband. Thus, the reconstructed image's resolution is not sacrificed to improve the target's velocity estimator. >

This paper presents a method to improve the SAR image of mine-type targets from wideband radar data that contain spectral gaps. The key concept that is exploited here is the correct identification of where the radar energy gaps map into in the ground-plane spectral domain of a targetis SAR image as a function of the targetis coordinates (particularly, its depression angle) as well as the radar system parameters. Once this is established, we apply an iterative method to recover the missing data in the targetis spectral signature. This scheme is capable of not only suppressing the undesirable side-lobes but also recovering subtle coherent (phase) information in the targetis SAR signature. Results using data from a low-frequency ultra-wideband synthetic aperture radar (SAR) designed by Mirage System will be presented.

This work is concerned with developing radar signaling strategies and algorithms that enhance the performance of a synthetic aperture radar (SAR) to image targets in the presence of digital radio frequency memory (DRFM) repeat jammers. The approach is based on a manipulation/alteration of the transmitted signal and/or its parameters in the fast-time domain at every position of the synthetic aperture (pulse repetition interval, PRI); this scheme is known as pulse diversity. In particular, we utilize a modulated form of the transmitted chirp signal and/or vary the rate of the chirp at each PRI; the modulation and/or the rate is varied from one PRI to another, and these variations are only known to the user. The merits of these pulse diversity methods are studied using the autocorrelation and cross-correlation of these signals. We also present a signal processing method for penalizing a DRFM jammer that tries to repeat the radar signal.

Along-track interferometry (ATI) is a SAR technique that can be used to detect moving targets and estimate radial velocities. This paper examines the possibility of generating the MTI statistic by utilizing a multi-channel ATI processing method. This method is based on a 2D adaptive filtering algorithm, called signal subspace processing, which was developed to blindly calibrate two channels of an along-track monopulse SAR system. The merits of this method are studied using both simulated data and real data from multi-channel airborne radar measurement (MCARM) system.

This paper is concerned with change detection in averaged multi-look SAR imagery. Averaged multi-look SAR images are preferable to full aperture SAR reconstructions when the imaging algorithm is approximation based (e.g., polar format processing), or motion data are not accurate over a long full aperture. We study the application of a SAR change detection method, known as signal subspace processing, that is based on the principles of 2D adaptive filtering (M. Soumekh, January 1999) and we use it to recognize the addition of surface landmines to a particular area under surveillance. We identify the change detection problem as a trinary hypotheses testing problem, and identify a change signal and its normalized version to determine whether there is i) no change in the imaged scene; ii) a target has entered the imaged scene; or iii) a target has exited the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are provided with a realistic X band SAR platform using averaged noncoherent multi-look and coherent single-look SAR imagery.

This paper is concerned with the issues associated with the suppression of radio frequency interference (RFI) for a synchronous impulse reconstruction (SIRE) ultra-wideband (UWB) synthetic aperture radar (SAR) that is currently being designed and built at the Army Research Laboratory. In this effort, we are developing the next version of the UWB radar that can employ inexpensive A/D converters to digitize wideband signals using the equivalent time sampling technique. In this presentation, we provide an analytical model for the signature of the RFI sources that are measured via an equivalent time sampling scheme. This formulation reveals spectral as well as temporal properties of the measured RFI signals that would aid a user in developing sniff (passive) data collection strategies for constructing adaptive digital signal processing methods for suppressing RFI sources.

Modern Synthetic Aperture Radar (SAR) signal processing algorithms could retrieve accurate and subtle information regarding a scene that is being interrogated by an airborne radar system. An important reconnaissance problem that is being studied via the use of SAR systems and their sophisticated signal processing methods involves detecting changes in an imaged scene. In these problems, the user interrogates a scene with a SAR system at two different time points (e.g. different days); the resultant two SAR databases that we refer to as reference and test data, are used to determine where targets have entered or left the imaged scene between the two data acquisitions. For instance, X band SAR systems have the potential to become a potent tool to determine whether mines have been recently placed in an area. This paper describes an algorithm for detecting changes in averaged multi-look SAR imagery. Averaged multi-look SAR images are preferable to full aperture SAR reconstructions when the imaging algorithm is approximation based (e.g. polar format processing), or motion data are not accurate over a long full aperture. We study the application of a SAR detection method, known as Signal Subspace Processing, that is based on the principles of 2D adaptive filtering. We identify the change detection problem as a binary hypothesis-testing problem, and identify an error signal and its normalized version to determine whether i) there is no change in the imaged scene; or ii) a target has been added to the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are provided for data collected by an X band SAR platform and processed to form non-coherently look-averaged SAR images.

Methods that include diffraction effects are discussed for the tomographic reconstruction of the complex index of refraction within a soft-scattering object. The methods are Fourier-domain based and are threfore computationally efficient. An important signal-processing issue is shown to be the determination of the unwrapped phase of the sensed fields. The theoretical presentation is followed by examples of experimental results.

This paper presents a new view of the problem of image reconstruction in the spatial Fourier domain based on the generalized projections of a two-dimensional image. The algorithms that are presented are derived from the exact continuous relations between the Fourier transforms of a spatially limited image and those of its generalized projections. A Fourier domain reconstruction formula is derived that is a natural consequence of these relations giving values of the two-dimensional transform on a regular grid useful for inverse FFT. This approach is contrasted with the more ad hoc methods of Fourier domain interpolation and with the spatial domain approaches such as the backprojection and backpropagation methods.

Theoretical, algorithmic and experimental results on the use of Rytov's approximation in acoustic tomography are presented. The approximation error is related to the disturbance size and magnitude. A method of phase unwrapping which is based on a combination of profile to profile phase comparison coupled with some well-known phase unwrapping algorithms used in signal processing is introduced. Frequency and spatial domain reconstructions are compared with respect to computational efficiency and accuracy of interpolation.

This paper addresses the problem of reconstructing a bandlimited signal from a finite number of its unevenly-spaced sampled data. We present the main results for a Fourier analysis of the available data [10] done in a framework similar to Shannon's sampling theorem for evenly-spaced data. The results are then utilized to determine the required constraints and algorithms for accurate reconstruction.

This paper addresses the problems of image reconstruction in fan beam straight-path tomography from complete and incomplete data. A method for restoring the parallel beam projections of an object from its fan beam projections is introduced. The scheme utilizes FFT routines for this purpose. It is shown that the approach reduces the required amount of the collected fan beam data by half. Moreover, a noniterative method of image reconstruction, when arbitrary segments of the object projections cannot be detected, is presented. The technique exploits the functional properties of the object projections, in conjunction with a priori information available about the test object, to restore the unknown data.

In support of the U.S. Army Night Vision And Electronic Sensors Directorate (NVESD), the U.S. Army Research Laboratory (ARL) has developed infrastructures, tools, and algorithms to evaluate the data set. This paper focuses on the signal processing and image formation using data from a low-frequency ultra-wideband sensor. We examine various issues that are associated with this class of SAR databases such as radio frequency interference (RFI), the effects of spectral notches, and errors in motion measurement to image quality. We show the pre-processing steps such as frequency and phase calibration, radio frequency interference extraction. We also show the application of digital spotlight technique to correct motion errors introduced by the measurement system. Finally, we show the resulting SAR imagery of various minefields.

This paper is concerned with suppressing multiple wide-bandwidth radio frequency interference (RFI) sources in SAR systems. A coherent processing of passive radar (sniff) data is presented to diminish the effects of wide-bandwidth as well as narrow-bandwidth RFI sources in the active radar data that are collected by a SAR system. The approach is based on a two-dimensional adaptive filtering of the active SAR data using the passive sniff data as the reference signal. A similar mathematical (signal) model and processing is also utilized to suppress self-induced resonance (SIR) signals that are generated by the interaction of the radar-carrying platform and the transmitted radar signal. Results are shown using the Army Research Laboratory (ARL) low-frequency, ultra-wideband (UWB) imaging radar (Boom-SAR).© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper examines signal processing methods for improving the fidelity of backprojection SAR imagery using a preprocessing method that suppresses Doppler aliasing as well as other side lobe artifacts that are introduced by the radar radiation pattern. The algorithm, known as digital spotlighting, imposes a filtering scheme on the azimuth-compressed SAR data, and manipulates the resultant spectral data to achieve a higher PRF to suppress the Doppler aliasing. The merits of the algorithm are studied using the ARL boom-SAR data.

This paper introduces an adaptive method for rejecting clutter in forward-looking infra-red (FLIR) imagery. In this approach, a spatially-varying two-dimensional adaptive filtering method is developed to identify a metric distance (error energy) between a test scene and a library of reference man-made targets (trucks, tanks, etc.). The function of the 2D spatially-varying adaptive filter is to compensate for: a) variations of image point response (IPR) of a FLIR sensor; b) variations of heat distribution on the test and reference targets; c) subpixel shifts in the relative coordinates of these targets; and d) subtle scaling and rotations. A statistic is constructed that is the least square energy of the error between the test target and its projection into each member of the library of reference target chips based on the above-mentioned spatially-varying 2D adaptive filtering; this database is then used to identify the test chip as a man-made target or clutter. Results with FLIR data of scenes composed of trucks, tanks, and APCs at various angles in different types of clutter environment will be provided.

This paper examines coherent signal processing methods for combining the data that are collected via multi-channel airborne radar system for MTI/GMTI. We study the methods that convert multi-channel radar data into dual along-track monopulse SAR signals of the radiated scene. A 2D adaptive filtering method, that projects the data in one synthesized SAR channel into the signal subspace of the other, is used for blind calibration of the monopulse SAR signals and generation of the MTI statistic. The merits of these algorithms are studied using the data from the multi-channel airborne radar measurement (MCARM) system that has been developed by the Air Force Research Laboratory at Rome, New York.

The paper addresses the problem of calibrating FLIR images of a scene that are acquired at different time points to construct information for moving target indication (MTI) and change detection. A signal model is developed to identify variations and imperfections of an FLIR sensor in time. This model is utilized to compensate for relatively slow variations of a bias in the FLIR sensor via a Fourier-based processing. Furthermore, a two-dimensional adaptive filtering method is developed to compensate for variations of the image point response (IPR) of a FLIR sensor as well as sub-pixel changes in the relative coordinates of the sensor-target over time. Results with time series FLIR, data of a scene with an airborne helicopter and a ground target are provided.

Physicians can encounter problems in prescribing opioids for some patients with chronic pain such as multiple unsanctioned dose escalations, episodes of lost or stolen prescriptions, and positive urine drug screenings for illicit substances. This study explored the usefulness of questions on abuse history in predicting problems with prescribing opioids for patients at a hospital-based pain management program. One hundred forty-five (145) patients who were taking long- and short-acting opioids for their pain were classified as high or low risk on the basis of their responses to interview questions about 1) substance abuse history in their family, 2) past problems with drug or alcohol abuse, and 3) history of legal problems. The treating physicians completed a questionnaire about problems that they had encountered with their patients. Problem behaviors were verified through chart review. No differences in demographic characteristics were found between those classified as high and low risk. Patients who admitted to a family history of substance abuse, a history of legal problems, and drug or alcohol abuse were prone to more aberrant drug-related behaviors, including a higher incidence of lost or stolen prescriptions and the presence of illicit substances in their urine (P < 0.05). Patients classified as high risk also had a significantly higher frequency of reported mental health problems and motor vehicle accidents. More of these patients smoked cigarettes, tended to need a cigarette within the first hour of the day, took higher doses of opioids, and reported fewer adverse effects from the medications than did those without such a history (P < 0.05). This study demonstrates that questions about abuse history and legal problems can be useful in predicting aberrant drug-related behavior with opioid use in persons with chronic noncancer pain.

Image registration is one of the crucial steps in detecting changes among the time series medical images. Due to variations in the imaging system over time, the impulse response of the imaging system, also known as its point spread function (PSF), exhibits a time-varying behavior. The registration is further complicated due to the subtle coordinate changes introduced by the patient. In this work, the registration problem is approached via a spatially varying multi-dimensional adaptive filtering method that relates one image in terms of an unknown linear combination of the other image and its spatially transformed versions. Using this model, we develop a scheme, which we refer to as signal subspace processing, to estimate a localized impulse response to calibrate relatively small regions. A criterion is designed to identify the localized PSFs that are not sensitive to the system noise or anatomical changes but accurately represent the spatially varying nature of the unknown miscalibration sources. Low order polynomials are used to sew the localized PSF together and construct a global spatially variant PSF. The anatomical changes between the time series images are achieved by calibrating the image with the global spatially variant PSF. Numerical experiments using MR images illustrate the effectiveness of the proposed algorithm.

This paper addresses the problem of developing signal processing, moving target detection, and image formation algorithms, for an airborne array radar system, called Multi-Channel Airborne Radar Measurement (MCARM), developed by the Air Force Research Laboratory at Rome, New York. Our approach is based on interpreting the MCARM data via a multichannel SAR system. SAR imaging and blind calibration of a dual along-track SAR-MTI system are then used for the MCARM data.

This paper examines two applications of a multi-channel airborne radar system, or an array-based synthetic aperture radar (SAR). The first mode involves a stripmap SAR array whose electronically-steered beam patterns are exploited to achieved the azimuth resolution of its single element while maintaining a relatively high radar power; this system has applications in foliage penetrating (FOPEN) SAR. The second array-based SAR utlilizes two or more elements in the along-track domain to detect moving targets. Signal processing issues associated with these two array-based SAR systems are discussed.

Summary form only given. The problem of echo imaging when the imaging system is composed of a group of phased arrays with arbitrary coordinates in the spatial domain (multistatic configuration) has been addressed. Each phase array has a finite aperture and is used for transmitting, receiving, or both functions. A receiving phased array may make a synchronous or asynchronous detection of the backscattered signal. The task in this imaging problem is to integrate the data collected by the phased arrays and relate them to the object under study. The imaging problem is first formulated for a plane wave source in a bistatic configuration. These results are extended for the radiation patterns of a multistatic imaging system. Methods for processing the backscattered signals to reduce the artifacts in the reconstructed image caused by the finite size of the phased arrays have been developed. Phase processing techniques have been examined for the case in which the backscattered signal is detected in a noncoherent environment. It has been shown that these array processing principles can be utilized to formulate a system model and inversion for synthetic aperture radar imaging that incorporates wavefront curvature. >

Examines the implications of reconstruction based on measurements of echoed waves from an object. The Helmholtz wave equation model is used for the inversion (diffraction imaging). It is shown that the resultant inverted data provides coverage in a one-quadrant of the spatial frequency domain. This coverage yields accurate information regarding the surface structure of the object under study. >

Addresses the problem of reconstructing an image from two pairs of its orthogonal projections. The range and support information of the image function is utilised in conjunction with the available projections to develop an iterative reconstruction method; the iterative algorithm is an error energy reduction scheme. Reconstruction results for two classes of image functions are presented. >

This paper presents a method for range-speed imaging of moving targets. The approach is based on illuminating the target region with an FM-CW signal. The inversion in this imaging problem involves a partitioning of the echoed signals in the frequency domain followed by a transformation. The system model and inversion in this imaging method does not approximate a moving target's Doppler shift to be a constant over the bandwidth of the transmitted signal and does not put any restrictions on the target's range.

The paper presents a method for imaging from the data obtained from a synthetic aperture radar that does not utilize spotlighting. The SAR database, that is commonly encountered in reconnaissance imaging with stripmap SAR, is passed through a digital spotlighting algorithm for range and cross-range gating. The resultant filtered SAR data is used in the high-resolution spotlight SAR inversion to image the desired target area. A subaperture processing and coherent imaging method to implement the algorithm is presented. >

The paper presents two applications of continuous-wave large-band width signaling, also known as FM-CW signaling, in imaging problems that involve moving targets or moving transmitting/receiving data acquisition systems. The first imaging system that is discussed is FM-CW synthetic aperture radar (SAR) imaging. In this imaging system, the echoed signal, that is recorded via a quasi-monostatic radar, is partitioned in its Fourier domain into bandpass regions (Doppler data) centered around the harmonics of the FM-CW signal, and then processed in the spatial Doppler-based inversion of pulsed SAR. The second imaging problem involves a quasi-monostatic or bistatic phased array system that utilizes FM-CW signaling for spatial-velocity imaging of a nonrigid moving target. the authors show that this phased array imaging system provides information regarding targets that are moving with a specific velocity vector on a specific contour of data in the spectral distribution of FM-CW phased array Doppler data. >

This paper presents a method for automatic detection of targets with nonlinear motion embedded in dynamic clutter. This is achieved via processing the targets' incoherent ISAR data that are less vulnerable to multiplicative noise (phase errors). It is shown that the incoherent ISAR signature of a target scene may be viewed as its baseband ISAR signature. Thus, the magnitude of an ISAR database that is severely contaminated with phase errors, i.e., incoherent ISAR data, may be used for ISAR detection of moving targets. Incoherent ISAR data in the fast-time and slow-time domain are transformed into another two-dimensional domain. The signature of a target in the transformed domain is shown to be localized based on its mid-point range and speed. This localized statistic is suitable for automatic, i.e., machine-based, detection of stationary as well as moving targets in the scene. >

Monostatic and bistatic synthetic aperture radar (SAR) imaging systems with wide-bandwidth continuous-wave (WB-CW) sources have been utilized for military reconnaissance. The WB-CW sources are less susceptible than FM-CW sources to electronic counter measures (ECM). The main shortcoming of the WB-CW microwave illumination is that its resultant SAR echoed signal is not composed of distinct Doppler spreadings around specific tones; this creates difficulties to formulate the image formation in the WB-CW SAR systems via the conventional pulse or FM-CW SAR imaging algorithms. The paper outlines a time domain correlation (TDC) processing method and a Fourier-based processing method for image formation in WB-CW monostatic and bistatic SAR systems. Results are provided.

This paper addresses the problem of fusing the information content of two uncalibrated sensors. This problem arises in registering images of a scene when it is viewed via two different sensory systems, or detecting change in a scene when it is viewed at two different time points by a sensory system, or via two different sensory systems or observation channels. We are concerned with sensory systems which have not only a relative shift, scaling and rotational calibration error, but also an unknown point spread function (that is time-varying for a single sensor, or different for two sensors). By modeling one image in terms of an unknown linear combination of the other image, its powers and their spatially-transformed (shift, rotation and scaling) versions, a signal subspace processing is developed for fusing uncalibrated sensors. The proposed method is shown to be applicable in moving target detection (MTD) using monopulse synthetic aperture radar (SAR) with uncalibrated radars. Results are shown for video, magnetic resonance images of a human brain, moving target detector monopulse SAR, and registration of SAR images of a target obtained via two different radars or at different coordinates by the same radar for automatic target recognition (ATR).

This paper presents a method for volumetric reconstruction from helical computerized tomography (H-CT) data which are collected with a fan beam source. An interpretation of the H-CT data in terms of the axial computerized tomography (A-CT) data is provided. This analysis indicates that the H-CT data for positive and negative detector angles can be combined to form periodically nonuniform hexagonal samples of the A-CT data. A Fourier-based method to reconstruct the A-CT data from this form of data coverage is presented. The target function is then reconstructed using the conventional fan beam computed tomography algorithms for A-CT.

This paper presents methods for detecting and identifying moving targets in a synthetic aperture radar (SAR) scene. An analytical expression is derived for the coherent SAR signature of a target. SAR system model of a moving target is developed. These principles are then used to construct a SAR signal statistic (energy function) in a parameter space which is defined by the target's coordinates, speed, and coherent SAR signature. Stochastic gradient techniques are used to search for the maximum point of this energy function which is located at the desired target's parameters.

This paper is concerned with signal processing issues that are associated with foliage penetrating (FOPEN) USA Navy NP-3 ultra-wideband (UWB) synthetic aperture radar. The digital signal processors that were developed for the NP-3 data commonly used a radar beamwidth angle that was limited to 35 degrees. Provided that the NP-3 radar beamwidth angle was 35 degrees, the NP-3 SAR system would approximately yield alias-free data in the slow-time Doppler domain. We show that the NP-3 data possess a 50-degree beamwidth angle within the entire 215-730 MHz band of the NP-3 radar that is imposed by the radar (radial) range swath gate. The 50-degree beamwidth of the NP-3 system results in slow-time Doppler aliasing within the frequency band of 444-730 MHz. We outline a slow-time processing of the NP-3 data, that we refer to as digital spotlighting and PRF upsampling, to minimize the Doppler aliasing. The digital spotlighting is also used for in-scene target calibration.

This paper presents the results of three-dimensional imaging of a T-72 tank using its angular azimuthal (turntable) and linear elevation synthetic aperture data at X band. This is achieved using an accurate and computationally-efficient wavefront (Fourier-based) reconstruction algorithm for elevation and circular (E-CSAR) data. The E-CSAR 3D images are then used to synthesize 2D spotlight and stripmap slant plane SAR images of the target at a desired range and squint angle. For this purpose, a procedure is introduced that incorporates the spatially-varying azimuthal and elevation Doppler signatures of individual reflectors on the target as well as the mean range, azimuth and elevation of the flight path. Results using the E-CSAR images of the T-72 tank are provided.