A Sparse Recovery Method on EPC-MIMO Radar System

Multiple-Input Multiple-Output Radar with Element-Pulse Coding (EPC) is a novel way to address the performance degradation caused by range ambiguity in space-time adaptive processing. In this paper, we use the sparse recovery method to solve the problem that EPC-MIMO has a large demand for independent and identically distributed (IID) samples. On the one hand, we use the Sparse Bayesian Learning (SBL) to achieve space-time spectral estimation under the small sample condition, and on the other hand, the use of prior knowledge, reduce the redundancy of the sparse recovery dictionary and improve the computational efficiency of the algorithm. The simulation results demonstrate the effectiveness of the proposed method.