Ground moving target indication using knowledge based space time adaptive processing

Abstract

Space-time adaptive processing (STAP) techniques promise to offer the best means to detect weak targets in severe dynamic interference scenarios. Traditionally, STAP techniques were developed for the detection of low RCS, high velocity airborne targets, well removed from main-beam clutter in Doppler. STAP algorithms are only now being used for ground moving target indication (GMTI) from an airborne reconnaissance platform. We present a practical approach to STAP incorporating three components: nonhomogeneity detection, statistical processing of measured data, and hybrid processing. This combined approach ties together previous research in different aspects of STAP into one algorithm. The algorithm is tested using measured data from the Multi-Channel Airborne Radar Measurements program with particular interest in ground moving target detection.