Off-Grid Sparse Spectrum Fitting for DOA Estimation with Unknown Mutual Coupling
Ziyu Jiang, Xianpeng Wang, Jingyu Cong, Xiang Lan · 2022 IEEE 5th International Conference on Electronic Information and Communication Technology (ICEICT) · 2022
In this paper, an algorithm based on sparse spectrum fitting is proposed to solve the problem of DOA off-grid estimation under the condition of unknown mutual coupling. In the proposed method, the influence of mutual coupling is firstly eliminated by constructing a selection matrix by exploiting the banded complex symmetric Toeplitz structure of the mutual coupling matrix. Then, in the process of sparse recovery based on signal covariance, additional variables are employed to describe the modeling error caused by off-grid DOA. Finally, the constraints of sparse recovery are optimized by the improved covariance estimation error and chi-square distribution. The effectiveness of the proposed method is verified by comparing the performance of the proposed algorithm with several existing DOA estimation methods and Cramer-Rao bound (CRB) through simulation experiments.