稳健协方差矩阵重构波束形成算法  

Robust adaptive beamforming based on covariance matrix reconstruction

作　　者：陆家威 童晖[1] 许伟杰[1] LU Jiawei;TONG Hui;XU Weijie(Shanghai Acoustic Laboratory,Chinese Academy of Sciences,Shanghai 201815,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院声学研究所东海研究站,上海201815 [2]中国科学院大学,北京100049

出　　处：《声学技术》2022年第1期131-136,共6页Technical Acoustics

摘　　要：针对信号导向向量失配以及接收数据协方差矩阵存在误差会导致传统的自适应波束形成器产生能损失的问题,提出了一种基于干扰加噪声协方差矩阵重构的稳健波束形成算法。该算法通过对信源来波角度范围进行Capon谱估计得出重构信源协方差矩阵,并通过特征分解以及子空间性质得出信源的导向向量,然后利用重构所得信源导向向量计算出信源功率以及噪声功率,从而得到重构干扰加噪声协方差矩阵,进而得出最优加权向量。仿真表明,该算法具有良好的稳健性,在快拍数较低的情况下,仍能保持良好的性能。Since the performance of traditional beamforming degrades when steering vector error and covariance matrix error are contained,an algorithm based on interference and noise matrix reconstruction is proposed to solve this problem in this paper.Firstly,the reconstructed covariance matrix is estimated by discrete summation of the signal and interference in their arrival region,then the steering vector corresponding to the reconstructed matrix is estimated by the eigenvector corresponding to the largest eigenvalue of the reconstructed matrix.The interference and noise matrix are calculated based on the power estimation.The interference power is calculated directly based on spectrum,the noise power is calculated by summing the Capon spectrum outside the desired signal and interference region,then the interference plus noise matrix is reconstructed,so that the optimal weighted vector is obtained.Simulation results show that,the proposed algorithm is well robust to steering vector error and element displacement error,and still works effectively when snapshots are limited.

关 键 词：导向向量估计 干扰加噪声协方差矩阵重构 自适应波束形成 

分 类 号：TN911.7[电子电信—通信与信息系统]