Performance evaluation of two polarimetric STAP architectures

Space-time adaptive processing (STAP) is a powerful technique for detecting slowly moving targets in strong clutter. However, STAP performance is limited when used on radars with small apertures. Past research suggests polarization´s potential to effectively discriminate between targets and clutter, thereby improving detection performance. We evaluate two methods of incorporating polarization into STAP, modeled after the polarimetric matched filter (PMF) and the polarimetric whitening filter (PWF). Our analysis serves to unify various proposed approaches to combining STAP and polarization, and benchmarks the benefits of polarization to GMTI detection. Using measured clutter and target characteristics from published sources as a baseline, we found that the PMF technique offers up to 6-dB improvement over STAP. This significant advantage is realized in the center of the clutter spectrum, and the impact on minimum detectable velocity (MDV) is modest. However, the PWF offers increased performance over the entire Doppler spectrum, and can be easily implemented as a STAP post-processor.