一种有限快拍情况下基于特征空间的稳健波束形成算法  

A robust eigenspace-based beamforming method in the situation of limited snapshots

作　　者：张妍洁[1] 周渊平[1] 

机构地区：[1]四川大学电子信息学院,成都市610000

出　　处：《四川大学学报（自然科学版）》2011年第2期339-342,共4页Journal of Sichuan University(Natural Science Edition)

摘　　要：有限快拍并在低信噪比(Signal to Noise Ratio,SNR)的情况下,广义旁瓣对消器(Generalized Side-lobe Canceller,GSC)能够将主波束对准期望信号方向,零陷对准干扰信号方向,从而最大程度的抑制干扰.但如果SNR过高且天线存在幅相误差,则可能将期望信号当做干扰同样被抑制.将接收信号的自相关矩阵进行特征分解,可以得到信号子空间与噪声子空间.基于特征空间的波束形成技术将常规的权矢量向此信号子空间投影,解决了高SNR情况下信号容易被抑制的问题.本文根据输入SNR的大小综合了前两者的优点,即无论在高SNR还是低SNR情况下,均能获得较高的输出信干噪比(Signal to Interference Plus Ratio,SINR),是一种稳健的自适应波束形成算法.In the situation of limited snapshots and low Signal to Noise Ratio （SNR）, the Generalized Side-lobe Canceller （GSC） focuses energy in the desired direction, which helps to reduce the interference. But if the SNR gets higher and there＇s any amplitude-and-phase error in the antennas, it may reduce the energy of desired signal as interference. The signal subspace and noise subspace can be obtained by eigen-decomposition of the correlation matrix of the input signal. The eigenspace-based beamforming method projects the normal weight vector onto this signal subspace to solve the problem of reducing the desired energy in the above situation. According to the input SNR, this paper synthesize advantages of both methods mentioned above, that is to say, whether the input SNR is low or high, it can obtain relatively high output Signal to Interference Plus Ratio （SINR）, which is a robust adaptive beamforming method.

关 键 词：旁瓣对消器 特征分解 特征空间 自适应 波束形成 

分 类 号：TN820[电子电信—信息与通信工程]