Jointly sparse recovery of multiple snapshots in STAP

A novel STAP algorithm based on jointly sparse recovery technique using multiple snapshots, called JSR-STAP, is proposed in this paper. The new algorithm uses the combined l_2,1 norm minimization to estimate the sparse spatial-temporal spectrum of measure data from the airborne array radar. Compared with traditional sparse recovery based STAP methods introduced in literature, the JSR-STAP extract a more reliable support set of clutter reflection from multiple snapshots so that the sparse recovery quality is evidently improved, and thus leads to a better result of clutter restrain. Both simulation and experimental results are provided to illustrate the performance of our new method.