基于迭代梯度方法的线性约束稳健Capon波束形成快速算法  

A Fast Algorithm for Linear Constrained Robust Capon Beamforming Based on Iterative Gradient Method

作　　者：郭翔宇 鄢社锋[1,2] 王文侠 GUO Xiangyu;YAN Shefeng;WANG Wenxia(Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,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,北京100190 [2]中国科学院大学,北京100049

出　　处：《信号处理》2021年第5期712-723,共12页Journal of Signal Processing

基　　金：国家自然科学基金资助项目(61725106)。

摘　　要：为了缩减线性约束稳健自适应波束形成算法的计算量,使之能够应用于单快拍更新的实时信号处理应用场景,本文提出了一种基于单快拍更新和迭代梯度方法的线性约束稳健Capon波束形成快速算法,将原始算法的O(M 3)时间复杂度优化到O(M 2)级别。该算法使用秩1更新维护算法所需的逆矩阵并计算波束加权值的线性约束部分,使用迭代梯度方法更新波束加权值的自适应部分,将两部分按照约束缩放后相加得到波束加权值。数值仿真表明该算法收敛快速,与原始算法有着几乎相同的性能。In order to reduce the amount of calculation of the linearly constrained robust adaptive beamforming algorithm,so that it could be applied to the real-time signal processing application scenarios of single-snapshot updating,this paper proposed a fast algorithm for linearly constrained robust Capon beamforming(LCRCB)based on single-snapshot updating and iterative gradient method,with the time complexity optimized from O(M 3)to O(M 2).The algorithm used rank-1 updating to maintain the required inverse matrix,calculated the linear constraint part of the weight,and used the iterative gradient method to update the adaptive part of the weight.The two parts are scaled and added according to the constraint to obtain the weight.Numerical simulation shows that the algorithm converges quickly and has almost the same performance as the original LCRCB.

关 键 词：阵列信号处理 稳健自适应波束形成 梯度下降 快速算法 

分 类 号：TN911.7[电子电信—通信与信息系统]