Multi-target localization for MIMO radar based on sparse representation

A new method is proposed for the multi-target localization of bistatic multiple-input multiple- output(MIMO) radar based on the sparse representation. Firstly, a redundant dictionary is built based on the two-dimensional scene where the targets locate. Then, a given number of eigenvectors as observation signals obtained from the covariance matrix of array received signals are sparsely denoted in the redundant dictionary, and constructed a multiple-measurement vectors(MMV)model, namely a low-dimensional sparse linear model which reduces the matrix dimension directly using the received signals as observation signals under the premise of containing angle information of the targets. Finally, angle estimation is obtained by the sparse recovery algorithm. Compared with the existing algorithm, the proposed algorithm reduces the computational complexity of directly reconstructing the original signals and performs well even under low SNR and low snapshots. The simulation results verify that the proposed method is effective.