【摘要】 针对有限采样数据样本中含有期望信号时自适应波束形成器性能下降的问题,提出了一种不需要任何参数设定的稳健自适应波束形成算法.该算法利用收缩方法得到一个增强的协方差矩阵估计值,替代传统的采样协方差矩阵,提高了算法的性能.为了克服信号导向矢量存在误差时对波束形成器性能的影响,对算法进行进一步的扩充,使其既能改善小快拍时协方差矩阵的估计值又能克服期望信号导向矢量的失配.仿真结果表明:该方法不仅能够改善小快拍情况下波束形成器的性能,而且还能克服期望信号导向矢量失配带来的不利影响.更多还原

【Abstract】 To solve the decrease of the performance in the adaptive beamformer in the situation of limited sample size,a robust beamforming algorithm without any parameters was proposed.This algorithm obtained an enhanced covariance matrix estimate via a shrinkage method,instead of the traditional sample covariance matrix,which improved the performance.In order to decrease the mismatch errors between the presumed and actual signal steering vectors,the algorithm was extended.The new derived algorithm is robust against covariance matrix uncertainty and the signal steering vector mismatch.Simulation results indicate that the proposed method can improve the performance in the case of small sample size and is robust against the signal steering vector mismatch.更多还原