[Show abstract][Hide abstract] ABSTRACT: Synthetic aperture image reconstruction applied to outdoor acoustic recordings is presented. Acoustic imaging is an alternate method having several military relevant advantages such as being immune to RF jamming, superior spatial resolution, capable of standoff side and forward-looking scanning, and relatively low cost, weight and size when compared to 0.5 - 3 GHz ground penetrating radar technologies. Synthetic aperture acoustic imaging is similar to synthetic aperture radar, but more akin to synthetic aperture sonar technologies owing to the nature of longitudinal or compressive wave propagation in the surrounding acoustic medium. The system's transceiver is a quasi mono-static microphone and audio speaker pair mounted on a rail 5meters in length. Received data sampling rate is 80 kHz with a 2- 15 kHz Linear Frequency Modulated (LFM) chirp, with a pulse repetition frequency (PRF) of 10 Hz and an inter-pulse period (IPP) of 50 milliseconds. Targets are positioned within the acoustic scene at slant range of two to ten meters on grass, dirt or gravel surfaces, and with and without intervening metallic chain link fencing. Acoustic image reconstruction results in means for literal interpretation and quantifiable analyses. A rudimentary technique characterizes acoustic scatter at the ground surfaces. Targets within the acoustic scene are first digitally spotlighted and further processed, providing frequency and aspect angle dependent signature information.
[Show abstract][Hide abstract] ABSTRACT: In this research, we have developed an algorithm to reduce the residual artifacts of the background clutter (that is, stationary targets) that appear in the MTI imagery that are generated by Global Signal Subspace Difference (GSSD) of the monostatic and bistatic images of an along-track monopulse synthetic aperture radar (SAR) data. We have also established the theoretical foundation for estimating the motion track and parameters of the detected moving targets. We will show the results of these algorithms on measured SAR data.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: Coherent signal processing methods for combining the data that are collected via a multi-channel airborne radar system for moving target detection and image formation, are examined. Methods that convert multi-channel radar data into dual along-track monopulse synthetic aperture radar (SAR) signals of the radiated scene, are studied. A two-dimensional adaptive filtering method that projects the data in one synthesised SAR channel into the signal subspace of the other, is used for blind calibration of the monopulse SAR signals and generation of the moving target indication statistic. The merits of these algorithms are studied using the data from the multi-channel airborne radar measurement system that has been developed by the Air Force Research Laboratory at Rome, New York
[Show abstract][Hide abstract] ABSTRACT: This letter describes the extension of signal subspace processing (SSP) to the arena of anomaly detection. In particular, we develop an SSP-based, local anomaly detector that exploits the rich information available in the multiple bands of a hyperspectral (HS) image. This SSP approach is based on signal processing considerations, and its entire formulation reduces to a straightforward (and intuitively pleasing) geometric and algebraic development. We extend the basic SSP concepts to the HS anomaly detection problem, develop an SSP HS anomaly detector, and evaluate this algorithm using multiple HS data files
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: This paper addresses change detection in averaged multilook synthetic aperture radar (SAR) imagery. Averaged multilook SAR images are preferable to full-aperture SAR reconstructions when the imaging algorithm is approximation-based (e.g., polar format processing) or when motion data are not accurate over a long full aperture. We examine the application of a SAR change-detection method, known as signal subspace processing, which is based on the principles of two-dimensional adaptive filtering, and we use it to recognize the addition of surface landmines to a particular area under surveillance. We describe the change-detection problem as a trinary hypothesis testing problem, and define a change signal and its normalized version to determine whether: 1) there is no change in the imaged scene; 2) a target has entered the imaged scene; or 3) a target has exited the imaged scene. A statistical analysis of the error signal is provided to show its properties and merits. Results are presented for averaged noncoherent multilook and coherent single-look X-band SAR imagery.
IEEE Transactions on Geoscience and Remote Sensing 01/2006; 44:201-213. · 3.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This report examines coherent signal processing methods for combining the data that are collected via a multichannel airborne radar system for moving target detection and image formation. We study methods that convert multi-channel radar data into dual along-track monopulse Synthetic Aperture Radar (SAR) signals of the radiated scene. A two dimensional (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 Moving Target Indication (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.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: 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.
Radar Conference, 2004. Proceedings of the IEEE; 05/2004
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: 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.
Radar Conference, 2003. Proceedings of the 2003 IEEE; 06/2003
[Show abstract][Hide abstract] ABSTRACT: 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.
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on; 05/2003
[Show abstract][Hide abstract] ABSTRACT: 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.
Signal Processing, 2002 6th International Conference on; 09/2002
[Show abstract][Hide abstract] ABSTRACT: Moving target detection and imaging results for an X band
spotlight synthetic aperture radar (SAR) system that utilizes an
along-track monopulse configuration for its data collection is
presented. The theoretical foundation of the processing that is used on
these data is based on our earlier work in which a two-dimensional
signal subspace processing (adaptive filtering) method was used to
calibrate the monostatic and bistatic radars of the monopulse SAR
system. The blind calibration of the two channels enables the user to
null the stationary scene, and detect the moving targets. Next, a
measure that we call SAR ambiguity function is used to estimate the
relative speed of a detected moving target. The resultant estimate is
then used to image the moving target
IEEE Transactions on Aerospace and Electronic Systems 02/2002; · 1.30 Impact Factor