一种极化鲁棒自适应子空间检测算法

A method of polarimetric robust adaptive target detection in Gaussian clutter and noise was presented. There potentially exist many reasons, such as imperfectly calibrated arrays, pointing errors, etc., which may lead to the detection loss due to the mismatch between the presumed target steering vector and the actual one. A subspace based robust detector against model imperfection was proposed by adding some steering vectors close to the presumed one in the subspace constraint. Simulation results show that the proposed method performs well in the case of large target steering vector error.