最小范数约束的改进MVDR波束形成算法
Minimum Norm Constraint Based MVDR Beamforming Algorithm
李涛 1孙心毅 1成建波1
作者信息
- 1. 中国人民解放军 92728 部队,上海 200436
- 折叠
摘要
针对传统的最小方差无畸变响应(MVDR)波束形成方法,难以有效均衡和同时优化干扰和噪声抑制的问题,提出一种基于最小范数解的改进算法.通过对阵列接收信号的自相关阵进行特征分解,取大特征值减去噪声功率及大特征值对应特征向量,构建线性约束方程的最小范数解,代替 MVDR 算法中的自相关阵的逆的形式形成加权系数,其中噪声功率由小特征值的平均值估计,获得的权系数对应于线性约束条件下的最小范数解.仿真分析表明,该算法能够有效地在干扰位置处形成零陷,利于后续在时间维的噪声滤波处理,较之于MVDR等算法有更好的干扰和噪声抑制性能.
Abstract
Aiming at the difficulty in effectively balancing and optimizing interference and noise suppression sim-ultaneously of the traditional minimum variance distortionless response(MVDR)beamforming algorithm,an improved MVDR beamforming algorithm based on biorthogonal decomposition was proposed in this paper.By eigen-decomposition of the autocorrelation array of the array received signal,the large eigenvalue was subtracted from the noise power and the corresponding eigenvector of the large eigenvalue,and the biorthogonal base of the array manifold matrix vector is constructed to replace the inverse form of the autocorrelation array in the MVDR algorithm to form the weighting coefficient.The noise power was estimated by the average of small eigenvalues.The obtained weight coefficients correspond to the minimum norm solution under the linear constraint.Simula-tion analysis showed that the algorithm could effectively form nulls at the interference locations,which was ben-eficial for subsequent noise filtering in the time dimension and had better interfere and noise suppression per-formance than MVDR algorithm.
关键词
自适应波束形成/最小方差无畸变响应/特征分解/最小范数Key words
adaptive beamforming/MVDR/eigen-decomposition/minimum norm solution引用本文复制引用
出版年
2024
NETL
NSTL
万方数据