Performance of a High-Resolution Polarimetric SAR Automatic Target Recognition System

■ Lincoln Laboratory is investigating the detection, discrimination, and classification of ground targets in high-resolution, fully polarimetric, syntheticaperture radar (SAR) imagery. This paper summarizes our work in SAR automatic target recognition by discussing the prescreening, discrimination, and classification algorithms we have developed; data from 5 km of clutter and 339 targets were used to study the performance of these algorithms. The prescreener required a low threshold to detect most of the targets in the data, which resulted in a high density of false alarms. The discriminator and classifier stages then reduced this false-alarm density by a factor of 100. We improved targetdetection performance by using fully polarimetric imagery processed by the polarimetric whitening filter (PWF), rather than by using single-channel imagery. In addition, the PWF-processed imagery improved the probability of correct classification in a four-class (tank, armored personnel carrier, howitzer, or clutter) classifier.