多子阵互耦条件下的一维波达方向估计及互耦自校正

One-Dimensional DOA Estimation and Self-Calibration Algorithm for Multiple Subarrays in the Presence of Mutual Coupling

该文研究多子阵(multiple subamays)阵元互耦条件下的波达方向(DOA)估计,假设阵列由多个位置已知的均匀线阵(uLA)组成,但线阵阵元间存在互耦效应。利用均匀线阵互耦矩阵的带状、对称’l'oeplitz性及多子阵互耦矩阵的块状对角特性,提出了一种解耦合波达方向估计及互耦自校正算法。该算法在未知阵元互耦参数的情况下, 可准确估计出信源的波达方向。另外,算法在精确估计波达方向的同时,还可准确估计出阵元间的互耦系数,实现多子阵的互耦自校正。算法的波达方向估计只需一维谱峰搜索,避免了通常多参数联合估计的多维非线性搜索及迭代运算,可明显减小算法运算量。文中讨论了算法参数可辨识性的必要条件,并分析计算了多参数联合估计的克拉美．罗界(CRB)。理论分析及蒙特卡罗仿真结果表明,该算法具有计算量小、DOA估计分辨力高、互耦校正效果好等优点。

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.