基于稀疏重构的稳健宽线性波束形成算法

Robust Widely Linear Beamforming Algorithm Based on Sparse Reconstruction

对于非圆信号,现有的宽线性波束形成算法要么在相干干扰源条件下性能急剧下降,要么对期望信号大的角度估计误差不稳健。针对此问题,提出一种基于稀疏重构的稳健宽线性波束形成算法。该算法首先通过引入稀疏渐进最小方差准则来估计信号功率和噪声方差,并以此来重构扩展的干扰加噪声协方差矩阵和估计期望信号扩展的导向矢量,进而获得宽线性波束形成器的最优权值向量。该算法所需的先验信息少,仅需已知天线阵列结构和期望信号所在的角度区域。该算法不仅对期望信号大的角度误差稳健,还能有效抑制相干干扰信号;同时它适用于任意阵列形状。与现有算法相比,仿真实验说明了所提算法具有更优的性能。

For noncircular signals,the existing widely linear(WL)beamforming algorithms will suffer from performance degradation when the interferences are coherent or the look-direction mismatch of the desired signal is large.In order to solve this problem,a new robust WL beamforming algorithm based on sparse reconstruction is proposed.Firstly,based on sparse asymptotic minimum variance approach,the signal power and noise variance are jointly estimated.Then,the signal power and noise variance are adopted to reconstruct the augmented interference-plus-noise covariance matrix and the desired signal’s extended steering vector is estimated.Only the prior knowledge of the angular sector,in which the desired signal and the antenna array geometry are located,are utilized in the proposed algorithm.The proposed method is not only robust against the large look-direction mismatch of the desired signal,but also can handle coherent or highly correlated interferences.Meanwhile,it is suitable for the antenna array with arbitrary geometry.Compared with the existing WL beamformers,simulation results demonstrate that the proposed algorithm can achieve better performance.