A robust colored-loading factor optimization approach for knowledge-aided STAP

A robust colored-loading factor optimization approach referred to as LWEC is newly proposed for colored-loading knowledge-aided STAP. The colored-loading factor is optimized to maximize the whitening ability of the colored-loaded clutter-and-noise covariance matrix (CNCM) of the cell under test (CUT) on selected secondary samples. The proposed approach is robust to accuracy degree heterogeneity of the a priori information in both the range domain and doppler domain for its ability to evaluate the performance of the colored-loaded CNCM of each range bin independently and conduct the optimization algorithm after the dimension-reduced process. Solution of the optimization function is proved to be unique. Numerical experiment results demonstrate the effectiveness and robustness of the proposed approach.