One-Dimensional DOA Estimation and Self-Calibration Algorithm for Multiple Subarrays in the Presence of Mutual Coupling
多子阵互耦条件下的一维波达方向估计及互耦自校正

The issue of Direction-Of-Arrival (DOA) estimation in multiple subarrays is addressed. It is assumed that an array is composed of several uniform linear arrays (ULAs) of arbitrary known geometry, but there are mutual coupling between sensors of each subarray. By using the banded, symmetric Toeplitz character of the ULAs and the block diagonal character of the multiple subarrays, a new decoupling DOA estimation and self-calibration algorithm is proposed. The new algorithm can provides accurate DOA estimation without the knowledge of mutual coupling. In addition, the mutual coupling coefficients for array self-calibration can be achieved simultaneously. Instead of multidimensional nonlinear search or iterative computation, the algorithm just uses a one-dimensional search and can reduce the computation burden. DOA identifiability issue for such arrays is discussed, and the corresponding Cramer-Rao Bound (CRB) is derived also. Monte-Carlo simulations illustrate that the proposed algorithm possesses the better performance of low computational complexity, high resolution and better accuracy of self-calibration.