Robust DOA Estimation for MIMO Radar in Unknown Nonuniform Noise and Mutual Coupling

摘要

In this paper, the DOA estimation issue for MIMO radar in unknown nonuniform noise and mutual coupling is addressed by proposing a robust sparse bayesian learning algorithm. In the proposed method, the influence of mutual coupling is eliminated by exploiting the banded complex symmetric Toeplitz structure of the mutual coupling matrices. Then a robust bayesian learning algorithm is formulated for DOA estimation, in which the covariances of unknown nonuniform noise are updated by using the least square(LS) strategy. Compared with the existing sparse signal recover based algorithms, the proposed method works well and provides better angle estimation performance in unknown nonuniform noise and mutual coupling. Simulation results are used to verify the effectiveness of the proposed method.