Sparse array quiescent beamformer design combining adaptive and deterministic constraints

In this paper, we examine sparse array quiescent beamforming for multiple sources in interference-free environment. To maximize the output signal-to-noise ratio (SNR), the beamformer design comprises two intertwined stages, the determination of beamforming weights and the reconfiguration of array structure. The SNR maximization may produce high sidelobe levels, making the receiver vulnerable to interferences. We consider the problem of achieving maximum SNR beamforming subject to specified quiescent pattern constraints and, as such, combine both adaptive and deterministic approaches for sparse array configurations. We employ two convex relaxation methods and an iterative linear fractional programming algorithm to solve the nonconvex antenna selection problem for sparse array beamformers. Simulation examples demonstrate that the array configuration plays a vital role in determining the beamforming performance in interference-free scenarios.