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