基于协方差匹配技术的互耦和幅相误差联合校正算法

The Joint Calibration Algorithms of Mutual Coupling and Gain-and-Phase Errors Based on Covariance Matching Technique

提出了基于协方差匹配技术的均匀线阵互耦和幅相误差联合校正算法.首先,根据协方差匹配技术中的目标函数和均匀线阵的误差模型,设计了一种交替迭代算法用以实现各种参数的优化计算.接着,为了避免该算法中的每轮循环迭代都需要进行波达方向估计这一复杂环节,利用理想条件均匀线阵协方差阵的Toeplitz性,给出了另一种改进型交替迭代算法用以减少计算复杂度.与基于子空间技术的阵列误差校正方法相比,文中的两种新算法可直接利用信源的统计特性,并且适用于不同的高斯噪声模型(例如噪声功率不一致),仿真实验验证了新算法的有效性和优越性.

The joint calibration method of mutual coupling and gain-and-phase errors based on covariance matching estimation technique（COMET） are proposed for the uniform linear array（ULA）.According to the cost function of the COMET and the errors model of the ULA,an alternative iteration algorithm is presented to optimize all the unknown parameters.In order to avoid the complicated step concerning the DOA estimation in each of iteration,an improved alternative iteration algorithm is presented to reduce the computation complexity via making use of the Toeplitz structure of the covariance matrix for the ULA.Compared with the errors calibration methods based on subspace technique,the two novel algorithms are capable of directly exploiting the time-domain statistical characteristic of the sources and are applicable to different Gaussian noise models,e.g.,the case of nonuniform noise power.The simulation experiments validate the effectiveness and advantage of the novel algorithms.