Sparsity-Based Robust Beamforming in the Presence of Fast-Moving Interference Signals

In this paper, we present a robust time-varying adaptive beamformer that employs a novel strategy for the suppression of fast-moving interference sources. By exploiting the sparsity of the interference sources, the parameters, which include the direction-of-arrival and power of the desired and interference signals as well as the noise power, are estimated, and then the interference-plus-noise covariance matrix is reconstructed. The proposed time-varying adaptive beamformer is compared with the state-of-the-art beamformers for mobile interference sources that employ a wide-null approach. It is demonstrated that the proposed beamformer achieves near-optimal performance and outperforms the wide-null beamformers in terms of the output signal-to-interference-plus-noise ratio performance.