基于协方差矩阵重构的稳健自适应波束形成算法综述

Review for Robust Adaptive Beamforming Based on Covariance Matrix Reconstruction

Capon波束形成器作为理论上最优的波束形成器具有良好的干扰抑制能力。然而Capon波束形成器对于模型失配误差非常敏感,尤其是针对协方差矩阵和期望信号导向矢量误差,波束形成器的性能会严重下降,这大大降低了波束形成器的稳健性。目前,一系列基于协方差矩阵重构的稳健自适应波束形成算法被提出,这些算法核心思想都是利用Capon功率谱一定的角度范围内积分来重构出协方差矩阵。本文首先介绍了波束形成的信号模型,然后在Capon波束形成器的基础上,介绍了4种基于协方差矩阵重构的稳健自适应波束形成技术,最后对未来波束形成技术的研究热点进行了展望。

The Capon beamformer,known as the optimal beamformer in suitable case,has the remarkable interferences suppression capability.However,the Capon beamformer is highly sensitive to the model mismatches.Especially when the covariance matrix and desired signal steering vector errors are existed,the performance of beamformer would degrade dramatically,which greatly reduces the robustness of the beamformer.Nowadays,a number of robust adaptive beamforming(RAB)algorithms based on the covariance matrix reconstruction have been proposed.The main idea of these algorithms utilizes the Capon power spectrum integrated in the special region to reconstruct the covariance matrix.In this paper,the signal model of beamforming is introduced firstly,and four typical covariance matrix reconstruction RAB algorithms are expounded based on the Capon beamformer.Finally,the future research directions are prospected.