Target Parameter Estimation in Reduced Dimension STAP for Airborne Phased Array Radar

Abstract

Space-Time Adaptive Processing (STAP) is an integral part of modern airborne phased array radars for slow-moving target detection. Conventional Pulse-Doppler radars estimate target parameters from the range-Doppler map. The estimated bearing of a target is limited by antenna beamwidth. STAP radar allows detection of targets in angle and Doppler domain. Hence, the target angle can be measured in a STAP radar without resorting to a monopulse feed network. In this study, we study methods to estimate target parameters for Reduced Dimension (RD) STAP radar. We apply STAP weights on the transformed input data to obtain a 3D processed array. The 3D array is projected onto a range vector and angle-Doppler domain. The target parameters are estimated by isolating peak response in the angle-Doppler projection of the detected range bin. The performance of the proposed algorithms is analyzed in terms of estimation accuracy as well as STAP metrics. Accuracy of angle and Doppler estimates were found to be improved by increasing spatial and temporal dimensions.