Joint Estimation Method of DOD and DOA of Bistatic Coprime Array MIMO Radar for Coherent Targets Based on Low-Rank Matrix Reconstruction

Based on low-rank matrix reconstruction theory, this paper proposes a joint DOD and DOA estimation method for coherent targets with bistatic coprime array MIMO radar. Unlike the conventional vectorization, the proposed method processed the coprime array with virtual sensor interpolation, which obtained a uniform linear array to generate the covariance matrix. Then, we reconstructed the Toeplitz matrix and established a matrix optimization recovery model according to the kernel norm minimization theory. Finally, the reduced dimension multiple signal classification algorithm was applied to estimate the angle of the coherent targets, with which the automatic pairing of DOD and DOA could be realized. With the same number of physical sensors, the proposed method expanded the array aperture effectively, so that the degree of freedom and angular resolution could be improved significantly for coherent signals. However, the effectiveness of the method was largely limited by the signal-to-noise ratio. The superiority and effectiveness of the method were proved using simulation experiments.

Automated summary

Based on the low-rank matrix reconstruction theory, this paper proposes a joint DOD and DOA estimation method for coherent targets using a bistatic coprime array MIMO radar. The proposed method effectively improves the angular resolution and degree of freedom for coherent signals by extending the array aperture with virtual sensor interpolation, generating the covariance matrix, reconstructing the Toeplitz matrix, and establishing a matrix optimization recovery model. The automatic pairing of DOD and DOA is achieved using the reduced dimension multiple signal classification algorithm. However, the effectiveness of this method is limited by the signal-to-noise ratio.