脉冲噪声下加权稀疏约束稳健波束形成方法

Robust Beamforming Method with Weigthed Sparse Constraint in Impulsive Noise

针对脉冲噪声下现有稀疏约束波束形成方法,对不同角度信号施加相同稀疏约束而带来干扰抑制能力有限的问题,本文提出了一种干扰抑制能力更优的加权稀疏约束稳健波束形成方法。该方法首先利用波束方向图的稀疏特性,在最小散度无畸变响应波束形成的目标函数中加入波束方向图l1范数约束;然后采用基于无穷范数归一化方法对阵列接收到的所有快拍信号做自适应预处理,以使预处理后的阵列接收信号协方差矩阵有限;最后运用传统的基于协方差矩阵特征分解的子空间法构造加权矩阵并应用到稀疏约束项中,使得波束方向图中不同角度的信号得到不同程度的约束。实验仿真表明,所提出方法不仅保持相对较低的旁瓣增益,而且显著加深了干扰方向的零陷,提高了输出信干噪比。

For impulsive noise environments,a weighted sparse constraint on beam pattern is proposed to improve the limited interference suppression ability of the existing sparse constraint-based beamformers,which impose a same constraint on all signals from different directions. Firstly,a l1-norm sparse constraint is incorporated into the objective function of the minimum dispersion distortionless response beamformer by exploiting the sparsity of the beam pattern. Then,in order to force the covariance of the array received signal finite,the infinity-norm normalization algorithm is employed to adaptively pre-processed all snapshots received by the sensor array. Finally,a weighted matrix,which is constructed using the traditional subspace method based on eigen-decomposition of the obtained covariance matrix,is applied to sparse constraint term so as to enforce different constraints on signals coming from different angles. The experimental results show that the proposed beamformer not only keeps the relative low sidelobe level,but also deepens the null in the direction of the interferers significantly,which results in an improvement of the output SINR.