自适应波束形成算法  

Adaptive Beamforming Algorithm

作　　者：焦圣喜[1] 王睿[1] 李婉珍[1] 

机构地区：[1]东北电力大学自动化学院,吉林吉林132012

出　　处：《信息与控制》2015年第2期165-170,共6页Information and Control

基　　金：国家自然科学基金资助项目(41076060);吉林省自然科学基金资助项目(20130101056JC);内蒙古大学高层次人才引进科研启动基金资助项目(135123)

摘　　要：针对线性约束最小方差(linearly constrained minimum variance,LCMV)自适应算法中存在的导向矢量误差敏感、协方差矩阵求逆计算量大等问题,提出一种改进的LCMV波束形成方法.通过变步长的最小均方(least mean square,LMS)算法求解最优权值矢量,避免了求逆运算,降低了固定步长对算法性能的影响,采用4阶累积算法解决了假设导向矢量存在误差的问题.仿真结果表明,变步长LMS-LCMV算法不但能自适应地估计导向矢量且具有更快的收敛速度和较小的稳态误差.The linearly constrained minimum variance （LCMV）adaptive algorithm has some deficiencies,inclu-ding sensitivity to steering vector error and large calculation requirements for the inversion of the covariance matrix.To solve these aforementioned issues,we propose an improved LCMV beamforming algorithm,which uses a variable step-size least mean square （LMS）algorithm to obtain the optimal weight vector.This algo-rithm avoids the inversion calculation and reduce the influence on the performance the algorithm caused by the fixed iteration step size.The problem with the steering vector direction is solved by using a fourth-order cumu-lant algorithm.Simulation results indicate that the proposed LMS-LCMV algorithm not only can adaptively es-timate the steering vector,but that it also has a faster convergence rate and a smaller steady-state error.

关 键 词：自适应波束形成 线性约束最小方差算法 最小均方算法 导向矢量 

分 类 号：TN911[电子电信—通信与信息系统]