火力与指挥控制2016，Vol.41Issue(3)：36-38,47,4.
高阶累积量自适应波束形成的改进算法
Improved Adaptive Beamforming Algorithm Based on Higher Order Cumulant
摘要
Abstract
For the Linear Constrained Minimum Variance (LCMV) algorithm in adaptive beamforming,there are sensitive to noise and the Signal-to-Noise Ratio(SNR)when beam forming by the small eigenvalue perturbation influence situation. In this paper,an improving method is proposed based on LCMV algorithm of high order cumulant . The method first calculates the higher-order cumulants of the received data of array,then the high order cumulant structure data augmented matrix singular value decomposition to calculate the pseudo inverse ,and pseudo inverse weight correction LCMV ,adaptive beamforming. The simulation results show that compared to the traditional LCMV algorithm and LCMV algorithm based on higher order cumulants. This algorithm can effectively overcome the adverse effects of disturbance on the signal to noise ratio increased when the beam forming small eigenvalues,and at a relatively low number of snapshots is still effective beamforming.关键词
高阶累积量/波束形成/线性约束最小方差准则/奇异值分解Key words
high order cumulant/beamforming/linearly constrained minimum variance/singular value decomposition分类
电子信息工程引用本文复制引用
高杨,李东生..高阶累积量自适应波束形成的改进算法[J].火力与指挥控制,2016,41(3):36-38,47,4.基金项目
国家自然科学基金面上资助项目 （）
