摘要
提出了一种新的基于协方差矩阵重构的稳健算法。该算法基于最小化输出期望信号空间倒谱,利用多项式拟合估计期望信号的导向矢量;从数据协方差矩阵中减去期望信号部分,得到干扰加噪声协方差矩阵,通过修正方法实现对干扰加噪声协方差矩阵的准确估计,解决了低信噪比时由于信号子空间发生缠绕,导致协方差矩阵估计存在较大误差的问题;理论分析与仿真实验表明了该算法的有效性和稳健性。
A novel robust algorithm was proposed. In contrast to previous works,the true desired signal steering vector was estimated by solving an optimization problem,and a computationally efficient steering vector estimator has been proposed by polynomial function. The interference-plus noise covariance matrix can be reconstruction by subtracting the desired signal component from the sample covariance matrix.However,when the desired signal presented in the training data is weak,the signal subspace will suffer from the high probability of subspace swap,and as a result,the desired power associated with desired signal will deviate from its true value severely. To prevent the absence of the desired signal steering vector in the estimated signal-plus-interferences subspace, we defined the modified interference-plus noise covariance matrix. The main advantage is that the proposed algorithm is robust against unknown arbitrary type mismatches. Theoretical analysis and simulation results demonstrate the effectiveness and robustness of the proposed algorithm.
作者
陈明建
龙国庆
黄中瑞
CHEN Ming-jian LONG Guo-qing HUANG Zhong-rui(Electronic Engineering Institute, Hefei 230037, Chin)
出处
《兵器装备工程学报》
CAS
2017年第4期1-7,共7页
Journal of Ordnance Equipment Engineering
基金
安徽省自然科学基金项目(1608085QF140)
关键词
稳健自适应波束形成
协方差矩阵重构
导向矢量估计
信干噪比
robust adaptive beamforming
covariance matrix reconstruction
steering vector estimation
signal to interference plus noise ratio
