基于凸约束下泰勒估计的主瓣干扰抑制算法

Mainlobe interference suppression based on the convex constrained Tyler's estimator

针对真实信号协方差矩阵估计难以直接获取及低快拍条件下传统采样协方差矩阵存在较大误差的问题,提出了基于凸约束下泰勒估计的抗主瓣干扰波束形成算法。该算法首先利用凸约束下的泰勒估计法在低快拍数条件下对信号协方差矩阵进行估计。其次利用多信号分类算法进行波达方向估计,筛选主瓣干扰对应特征矢量。而后利用特征投影矩阵法对主瓣干扰进行抑制。最后,通过添加线性约束获得权值矢量进行波束形成。仿真结果显示,在低快拍数条件下,所提算法对信号协方差矩阵具有更高的估计精度,波束形成性能稳健且具有更高的输出信干噪比。

In practice,due to the fact that the real signal covariance matrix can not be directly acquired,the sample covariance matrix(SCM)is usually used to replace the real covariance matrix,which will cause a large estimation error under the low snapshots condition.According to this problem,a beamforming algorithm for mainlobe interference suppression based on convex constrained Tyler’s estimator is proposed.Firstly,the convex constrained Tyler’s estimator is used to obtain the estimation of signal covariance matrix under low snapshots condition.Secondly,screening the eigenvector of the mainlobe interference by utilizing the multiple signal classification direction of arrival(DOA)estimation algorithm,and then the eigen-projection matrix preprocessing(EMP)method is used to suppress the mainlobe interference.Finally,the adaptive weight vector is obtained by linear constraint method.Simulation results demonstrate that the proposed method can achieve higher effectiveness and stronger robustness under low snapshots condition.