A sparse representation scheme for angle estimation in monostatic MIMO radar

In this paper, the problem of direction of arrival (DOA) estimation for monostatic multiple-input multiple-output (MIMO) radar is addressed, and a sparse representation scheme for DOA estimation is proposed. Firstly, the reduced-dimensional transformation matrix and SVD-technique are utilized to reduce the computational complexity of the sparse signal reconstruction. Then the coefficients of the reduced-dimensional Capon (RD-Capon) spectrum are exploited to design a weight matrix for reweighting l1 norm constraint minimization to enhance the sparsity of the solution, and the DOA can be estimated by finding the non-zero rows in the recovered matrix. The angle estimation performance of the proposed method is better than RD-ESPRIT and RD-Capon algorithms. Furthermore, the proposed method works well for coherence targets without any decorrelation procedure, and has low sensitivity to the priori information of the target number. Simulation results verify the effectiveness of the proposed method.