A blind least-squares approach to STAP using MCARM data

Adaptive array processing algorithms have received much attention in the past three decades. Previous techniques have focused on statistical methods based on estimating covariance matrices. However the estimates are often inaccurate or inapplicable especially in dynamic environments. A novel technique is proposed to simultaneously estimate phase and amplitude (SEPA) of narrowband signals in highly non-homogeneous environments. A geometric interpretation of SEPA as a minimum norm operator is presented and two specific norms are investigated The algorithm is then applied to the multi-channel airborne radar measurement (MCARM) data set. Targets are clearly detected in this severely cluttered scenario.