摘要 :
In recent years, synthetic aperture radars (SARs) have been used to detect man-made targets and to distinguish them from naturally occurring background. This paper continues development of a fundamental, physics-based approach to ...
展开
In recent years, synthetic aperture radars (SARs) have been used to detect man-made targets and to distinguish them from naturally occurring background. This paper continues development of a fundamental, physics-based approach to assessing the performance of SAR-based automatic target recognition (ATR) systems. A major thrust of this effort is to quantify the performance advantages that accrue when the recognition processor exploits the detailed signatures of the target's component reflectors, e.g.. their specularity, their polarization properties, etc. Its purpose is to assess target classification performance of a SAR-based ATR, starting from a foundation of rigorous, physics-based signal models developed from the electromagnetic scattering theory. New lower and upper bounds on the probability of correct classification (PCC) are developed for targets composed of a constellation of geometrically-simple reflectors. The performance discrepancy of a conventional full-resolution processor with respect to an optimal whitening-filter processor is discussed.
收起
摘要 :
We investigate passive radar imaging of aircraft using reflected TV signals. Such passive multistatic "radar'' has been developed to detect and track aircraft with good accuracy. The additional capability of image formation would ...
展开
We investigate passive radar imaging of aircraft using reflected TV signals. Such passive multistatic "radar'' has been developed to detect and track aircraft with good accuracy. The additional capability of image formation would help to identify targets. The Fourier space sampling provided by passive' radar is nonuniform. For a given aircraft flight path, different receiver locations give rise to different sampling patterns. We simulate multistatic radar returns using Fast Illinois Solver Code (FISC) and show that a good sampling pattern can be used to form a recognizable target image using direct Fourier reconstruction. However, a bad sampling pattern can make it impossible to form a useful image. In the Gaithersburg, MD area, we can select a good receiver location using 21 or fewer channels, which provides good enough Fourier-space coverage to form a useful aircraft image.
收起
摘要 :
In this paper we study the performance of two existing autofocus algorithms in a difficult SAR scenario. One algorithm is the well known phase gradient autofocus (PGA) algorithm and the other is the more recent AUTOCLEAN. The latt...
展开
In this paper we study the performance of two existing autofocus algorithms in a difficult SAR scenario. One algorithm is the well known phase gradient autofocus (PGA) algorithm and the other is the more recent AUTOCLEAN. The latter was introduced particularly with ISAR autofocus of a small target in mind and has been shown to outperform the PGA when range misalignment is present. This was expected as AUTOCLEAN, as opposed to PGA. has a built-in ability to compensate for range misalignment. In most available studies of the above autofocus algorithms spatially variant phase errors are absent or insignificant. The data used here is far-field SAR data collected over a large range of aspect, angles. The target area is large, hence significant motion through resolution cells (MTRC) occurs due to target, scene rotation. The polar format algorithm: (PFA) is applied prior to autofocus to handle MTRC and compensate for off-track platform motion. However, the platform motion measurements used in PFA are not precise enough to compensate for the off-track motion and left after PFA are phase errors corrupting the data. These phase errors are spatially variant due to the large target scene and this violates the models for the autofocus algorithms above. This in contrast with the previously mentioned studies. We show that the performances of the autofocus algorithms considered are much deteriorated by the presence of spatially variant phase error but in different ways since the averaging of the phase error estimates is made differently in the two algorithms. Based on our numerical study of the two autofocus methods we try to rank them with respect to their sensitivity to spatially variant phase errors.
收起
摘要 :
The Amplitude and Phase EStimation (APES) approach to amplitude spectrum estimation has been receiving considerable attention recently. We develop an extension of APES for the spectral estimation of gapped (incomplete) data and ap...
展开
The Amplitude and Phase EStimation (APES) approach to amplitude spectrum estimation has been receiving considerable attention recently. We develop an extension of APES for the spectral estimation of gapped (incomplete) data and apply it to synthetic aperture radar (SAR) imaging with angular diversity. It has recently been shown that APES minimizes a certain least-squares criterion with respect to the estimate of the spectrum. Our new algorithm is called gapped-data APES (GAPES) and is based on minimizing this criterion with respect to the missing data as well. Numerical results are presented to demonstrate the effectiveness of the proposed algorithm and its applicability to SAR imaging with angular diversity.
收起
摘要 :
The state-of-the-art in extremely versatile fine-resolution Synthetic Aperture Radar (SAR) systems allows incredibly fine resolution and accurate images to be formed over a wide range of imaging geometries (squint angles and depre...
展开
The state-of-the-art in extremely versatile fine-resolution Synthetic Aperture Radar (SAR) systems allows incredibly fine resolution and accurate images to be formed over a wide range of imaging geometries (squint angles and depression angles). This capability in turn is allowing the fusion of multiple views of targets and scenes into very accurate 3-dimensional renderings of the same scenes and targets. With proper imaging geometry selections, relative height accuracy within a scene can easily be on the order of the resolution of the original S AR images, thereby rivaling the finest IFSARs even on the drawing boards, and without the height ambiguities typically associated with large-baseline IFSARs. Absolute accuracy is typically limited to the accuracy of SAR flight path knowledge, bounded typically by GPS performance. This paper presents the relationship of height accuracy to imaging geometry (flight path) selection, and illustrates conditions for optimum height estimates. Furthermore, height accuracy is related to 3-D position accuracy and precision over a variety of imaging geometries. Performance claims of height precision on the order of resolution are validated with experimental results that are also presented, using multiple aspects of a target scene collected from a high-performance single-phase-center SAR.
收起
摘要 :
ATR using HRR-signatures have recently gained lot of attention. A number of classification methods have been proposed using different target descriptions. The traditionally used classifier utilizing mean square error between magni...
展开
ATR using HRR-signatures have recently gained lot of attention. A number of classification methods have been proposed using different target descriptions. The traditionally used classifier utilizing mean square error between magnitude only range profiles and templates suffers from problems with interfering scatterers. Several attempts to improve the MSE classifier both during the template formation process and in the matching have been made. We have recently presented a method that matches complex HRR signatures to target descriptions that use scattering centers. This method handle the unknown phases of the centers and thus overcomes the problem of interference between scatterers. In this paper we compare our method with a number of other methods that uses magnitude only range profiles. Those includes Mean-templates, Eigen- templates and the Specular and Diffuse scattering models.
收起
摘要 :
With the continuing interest in ATR, there is a need for high-resolution folly polarimetric data on tactical targets at all radar bands. Here we describe a newly developed system for acquiring W-band data with 1/16 scale models. T...
展开
With the continuing interest in ATR, there is a need for high-resolution folly polarimetric data on tactical targets at all radar bands. Here we describe a newly developed system for acquiring W-band data with 1/16 scale models. The NGIC sponsored ERADS project capability for obtaining fully polarimetric ISAR imagery now extends from X to W band. The high-frequency terahertz compact radar range developed recently to measure single polarization return from scale models of tactical targets has been enhanced to collect fully polarimetric data. The 1.56THz transceiver uses two high-stability optically pumped far-infrared lasers, microwave/laser Schottky diode side-band generation for frequency sweep, and a pair of Schottky diode receivers for coherent integration. Tactical targets may be measured in "free space" or on various ground terrain, which simulate different types of terrain. The results of recent polarimetric measurements on several tactical targets will be presented. Data collected using this compact range from a simulation target will also be compared with predictions from the XPatch computer code. In addition to conventional ISAR imaging the compact range is capable of imaging in both azimuth and elevation by collecting data and integrating it through a solid angle. Recent two-dimensional and three-dimensional measurements using this technique will be presented.
收起
摘要 :
Synthetic aperture radar (SAR) is an essential sensor for military surface surveillance because of its unique ability to operate day or night through weather, smoke and dust. Of particular importance is the problem of automatic ta...
展开
Synthetic aperture radar (SAR) is an essential sensor for military surface surveillance because of its unique ability to operate day or night through weather, smoke and dust. Of particular importance is the problem of automatic target recognition (ATR) which aims to identify targets of military significance within radar images. The Defence Evaluation and Research Agency (DERA) of the UK has a substantial programme of research into ATR algorithms for SAR battlefield surveillance. This covers both feature-based techniques which are the subject of this paper and model-based techniques. Feature-based ATR discriminates between target classes on the basis of the values taken by certain target features. The conventional approach is to select the best features for a particular task from a large set of features which have been pre-defined on the basis of physical intuition. A simple feature might be target area whilst a more sophisticated feature might be some measure of fractal dimension. ATR performance will be influenced by the type of features used and by the accuracy with which the statistical behaviour of these features has been characterised. This paper describes a technique which can be used to determine statistical feature behaviour despite limited examples of target realisations. It also addresses the problem of feature choice by introducing a method for adaptive feature design which automatically recognises the information not already contained in the existing feature set and develops a feature to represent this missing information. These ideas are illustrated by application to synthetic aperture radar (SAR) images of vehicles.
收起
摘要 :
Polarimetric synthetic aperture radar (POLSAR) provides additional information about the scatterers and clutter in a scene over that of single-band SAR. A fully polarimetric sensor contains four imaging channels that, when properl...
展开
Polarimetric synthetic aperture radar (POLSAR) provides additional information about the scatterers and clutter in a scene over that of single-band SAR. A fully polarimetric sensor contains four imaging channels that, when properly calibrated, can indicate the type of scatterers present. For example, it is possible to discriminate between trihedral-, dihehdral-, and dipole-like scatterers. The orientation of the scatterers can also be extracted. Based upon this additional information, hypotheses can be generated about the objects in the scene that are richer than those generated from single-band data. Combinations of transmission and reception with antennae that ideally represent orthogonal, balanced polarimetric states generate the four channels of the POLSAR system, In practice, the antenna elements are not perfect: crosstalk and imbalances exist between them, so that calibration is necessary. This paper addresses the calibration of POLSAR data, and introduces some new approaches to this problem. These include a novel gradient descent algorithm for crosstalk removal and the application of a rotating dihedral to the calibration of a sensor with receiver characteristics that are transmit-state dependent. The sensitivity of the Cloude~1 polarimetric decomposition to varying amounts of crosstalk and imbalance in an imperfectly calibrated data set is also discussed.
收起
摘要 :
We investigate the complexity of template-based ATR algorithms using SAR imagery as an example. Performance measures (such as P_(id)) of such algorithms typically improve with increasing number of stored reference templates. This ...
展开
We investigate the complexity of template-based ATR algorithms using SAR imagery as an example. Performance measures (such as P_(id)) of such algorithms typically improve with increasing number of stored reference templates. This presumes, of course, that the training templates contain adequate statistical sampling of the range of observed or test templates. The tradeoff of improved performance is that computational complexity and the expense of algorithm development training template generation (synthetic and/or experimental) increases as well. Therefore, for practical implementations it is useful to characterize ATR problem complexity and to identify strategies to mitigate it. We adopt for this problem a complexity metric defined simply as the size of the minimal subset of stored templates drawn from an available training population that yields a specified P_(id). Straightforward enumeration and testing of all possible template sets leads to a combinatorial explosion. Here we consider template selection strategies that are far more practical and apply these to a template-based SAR target identification problem. Our database of training templates consists of targets viewed at 3-degree increments in pose (azimuth). The template selection methods we investigate include uniform sampling, sequential forward search (also known as greedy selection), and adaptive floating search. The numerical results demonstrate that the complexity metric increases with intrinsic problem difficulty, and that template sets selected usingour greedy algorithmsignificantly outperform uniformly sampled template sets of the same size. The adaptive method, which is far more computationally expensive, selects template sets that outperform those selected by the greedy technique, but the small reduction in template set size was not significant for the specific examples considered here.
收起
