Sparse Recovery Algorithm of MIMO-STAP Based on Weighted SPICE

Aiming at the problem that the performance of airborne multi-input-multi-output (MIMO) radar space-time adaptive processing (STAP) technology is seriously degraded in the condition of nonhomogeneous clutter, the weighted SPICE sparse algorithm is introduced to recover the clutter spectrum. Weighted SPICE algorithm can incorporate a large class of sparse recovery algorithms into a unified framework, and LIKES, SLIM, IAA algorithms can be obtained according to different weighted vectors. These algorithms do not need to set any hyperparameter, and the unknown sparse parameters can be obtained through repeated iteration based on the clutter covariance matrix of training sample. The simulation experiment shows that using these sparse algorithms to recover the clutter spectrum can effectively improve the accuracy of the recovered clutter spectrum, and can better realize the moving target detection.