Optimum Sparse Array Receive Beamforming for Wideband Signal Model

Abstract

Sparse array design can potentially achieve comparable performance over uniform array counterparts with a fewer sensors. In this paper, we develop a sparse arrays design method achieving maximum signal-to-interference plus noise ratio (MaxSINR) for wideband source operating in a wideband jamming environment. The problem is formulated as quadratically constraint quadratic program (QCQP) that permits the use of weighted mixed $l_{1,\infty}$-norm squared penalization of the beamformer weight vector to achieve sparse array configurations. We propose the principal eigenvector based technique to control the desired group sparsity while promoting unit rank solutions iteratively. It is shown that the optimum sparse array utilizes the array aperture effectively and provides considerable performance improvement over commonly used arrays. Simulation results are presented to show the effectiveness of proposed algorithm for array configurability under wideband signal model.