Sen Ouyang / Harbin Institute of Technology, China
In this paper, a novel reconstruction algorithm based on compressed sensing under the background of large-scale array adaptive beamforming is proposed. Compared with traditional adaptive beamforming based on the covariance matrix high-dimensional reconstruction algorithm, the proposed approach for large scale adaptive beamforming could achieve more robust beamforming performance with the covariance mismatch conditions. Since the reconstructed signal with non-positive covariance matrix is sparse, modified method using diagonal loading technique is also considered. Moreover, owing to special spare character of compressed sensing, our proposed beamforming method make it possible to achieve higher degree of freedom (DOF) of beamformer with fewer sensors. Several results of numerical experiment demonstrate the effectiveness of the proposed approach.