Polarimetric STAP via Clutter Spectrum Reconstruction

Abstract

A new polarimetric space-time adaptive processing (pSTAP) approach is proposed to clutter suppression for weak target detection under short data samples. In the method, the target vector (also known as the target polarization-space-time steering vector) is determined based on the maximum likelihood scheme, while the clutter polarization-space-time spectrum (profile) is reconstructed by using a newly developed polarimetric sparse recovery technique. Numerical results are given to illustrate the performance of the proposed method.