Low-rank covariance matrix tapering for robust adaptive beamforming

Covariance matrix tapering (CMT) is a popular approach to improve the robustness of adaptive beamformers against moving or wideband interferers. In this paper, we develop a computationally efficient online implementation of the CMT technique based on a low-rank approximation of the taper matrix and the recursive least squares (RLS) algorithm. It is demonstrated that the performance of the proposed low-rank CMT approach is very close to that of the conventional CMT technique.