基于变分模态分解和优化递归最小二乘的自适应波束成形算法  

Adaptive Beamforming Algorithm Based on Variational Mode Decomposition and Optimized Recursive Least Squre

作　　者：李波 陈百菊 LI Bo;CHEN Baiju(School of Communications and Information Engineering^Xi'an University of Posts&Telecommunications^Xi'an 710100,China)

机构地区：[1]西安邮电大学通信与信息工程学院,陕西西安710100

出　　处：《信息与控制》2020年第6期722-727,734,共7页Information and Control

摘　　要：针对递归最小二乘(recursive least square,RLS)算法中存在的权值收敛较慢、零陷较浅等问题,提出了一种优化的RLS(optimized recursive least square,ORLS)波束成形方法.通过将线性约束最小方差(linearly constrained minimum variance,LCMV)算法中的线性约束部分加入到RLS算法中,解决了RLS算法中权值收敛速度较慢等问题.针对RLS算法在信噪比较低,遗忘因子较小的情况下,对噪声比较敏感且收敛误差较大的问题,提出了一种基于变分模态分解(variational mode decomposition,VMD)和ORLS的自适应波束成形算法.首先,该算法采用VMD对阵列接收信号进行降噪;然后,再利用ORLS算法进行波束成形.仿真结果表明,与传统的RLS算法相比,该算法具有较小的均方误差和较快的收敛速度,并且有更深的零陷,抑制干扰的能力更强.To address the problems of slow weight convergence and shallow nulling in the recursive least square( RLS) algorithm,we propose an optimized recursive least square( ORLS) beamforming method. By adding the linear constraint part of the linearly constrained minimum variance algorithm to the RLS algorithm,we solve problems such as the slow convergence speed of the weights in the RLS algorithm. To address the sensitivity of the RLS algorithm to noise and its large convergence error under the conditions of a low signal-to-noise ratio and small forgetting factor,we propose an adaptive beamforming algorithm based on variational mode decomposition( VMD) and ORLS. We use VMD to reduce the noise of the received signal array,and then use the ORLS algorithm for beamforming. Simulation results show that compared with the traditional RLS algorithm,the proposed algorithm has a smaller mean-square error and faster convergence speed,as well as deeper nulling and a stronger ability to suppress interference.

关 键 词：递归最小二乘算法 波束成形 变分模态分解 排列熵 降噪 

分 类 号：TN911[电子电信—通信与信息系统]