Space-Time Adaptive Processing for Side-Looking Arrays with Platform Maneuver

摘要

This research effort develops a space-time adaptive processing (STAP) radar data model for the side-looking (SL) array with platform maneuver. A primary assumption of most STAP models is the absence of platform maneuver during the coherent processing interval (CPI). This research abandons the platform stationarity assumption, allowing platform pitch, roll, and yaw during the CPI. The model developed characterizes platform maneuver effects on the clutter spectrum, examines Matched Filter (MF) output Signal-to-Interference- plus-Noise-Ratio (SINR), and investigates maneuver impact on sample support homogeneity. The introduction of pitch marginally impacts MF SINR due to the lack of achieved azimuth resolution in this research, but decreases available homogenous sample support 24% at 11 km and 20% at 66 km. Roll impact on MF performance is observed only in the planar array, with MF SINR dropping 4 dB but sample support homogeneity is unaffected. Yaw effects are the most devastating, dropping output SINR 15 dB at 11 km and 66 km, and decreasing available homogeneous sample support 34% at 11 km and 18% at 66 km.