互耦效应下低复杂度的二维DOA估计算法

互耦效应会对阵列流型产生扰动并改变子阵间的旋转不变关系, 导致二维子空间类算法性能急剧下降甚至失效。传统二维波达方向(two-dimension direction of arrival, 2D-DOA)估计和互耦校正算法存在二维谱峰搜索困难、迭代寻优慢和计算量大等问题。利用均匀矩形阵列的特殊结构以及互耦系数矩阵的特点, 提出了一种互耦效应影响下能实现完全解互耦的二维旋转不变子空间算法。该算法通过合理选取3个在互耦影响下仍具备旋转不变关系的子阵列, 构建扩展的协方差矩阵, 通过一次特征分解, 即可实现2D-DOA估计和互耦抑制。从理论上证明了ESPRIT算法应用于互耦效应影响下2D-DOA估计的可行性。算法无需二维谱峰搜索和阵列互耦任何信息, 计算量得到有效降低。仿真验证了该算法能够实现稳健的2D-DOA估计, 并抑制互耦效应影响, 估计性能与无误差时的标准ESPRIT算法接近。

Low complexity 2D-DOA estimation algorithm in the presence of mutual coupling

The performance of two-dimension subspace estimation algorithms degrades substantially because of the presence of mutual coupling by the perturbance of steering matrix and rotational invariance property. The classical two-dimension direction of arrival (2D-DOA) estimation and decoupling algorithms need multidimensional search, optimization and iteration, so it need large calucation quantity. Based on the special structure of the uniform rectangle array and the character istics of mutual coupling matrix, a decoupling two-dimension estimating signal parameter via rotational invariance techniques (2D-ESPRIT) algorithm in the presence of mutual coupling is proposed. The algorithm chooses three sub-arrays which maintain rotational invariance property in the presence of mutual coupling. An extended covariance matrixis is constructed. Decoupling and estimation of 2D-DOA can be accomplished via the eigen-decomposition of the matrix. The feasibility of rotational invariance techniques for application in 2D-DOA estimation in the presence of mutual coupling is proved. The algorithm requires neither 2D-searching spectrum peak nor the value of mutual coupling matrix, and the calculation quantity is reduced. The simulation results show that the algorithm can accurately estimate 2D-DOA and restrain mutual coupling. The estimation performance of the algorithm is equivalent to the standard ESPRIT algorithm without mutual coupling.