Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

TL;DR

This paper proposes a joint transmit-receive sparse array design for MIMO radar that optimizes MaxSINR beamforming using successive convex approximation and group sparsity, improving array efficiency.

Contribution

It introduces a novel joint sensor selection method for transmit and receive arrays in MIMO radar to enhance adaptive beamforming performance.

Findings

Effective antenna selection improves MaxSINR performance.

Joint design reduces system overhead and transceiver complexity.

Demonstrated success in various array configurations.

Abstract

Sparse array design aided by emerging fast sensor switching technologies can lower the overall system overhead by reducing the number of expensive transceiver chains. In this paper, we examine the active sparse array design enabling the maximum signal to interference plus noise ratio (MaxSINR) beamforming at the MIMO radar receiver. The proposed approach entails an entwined design, i.e., jointly selecting the optimum transmit and receive sensor locations for accomplishing MaxSINR receive beamforming. Specifically, we consider a co-located multiple-input multiple-output (MIMO) radar platform with orthogonal transmitted waveforms, and examine antenna selections at the transmit and receive arrays. The optimum active sparse array transceiver design problem is formulated as successive convex approximation (SCA) alongside the two-dimensional group sparsity promoting regularization. Several examples are provided to demonstrate the effectiveness of the proposed approach in utilizing the given transmit/receive array aperture and degrees of freedom for achieving MaxSINR beamforming.