Joint Active and Passive Beamforming for IRS-Assisted Radar

TL;DR

This paper proposes a joint active and passive beamforming approach for IRS-assisted radar systems to enhance target detection and robustness in cluttered environments, using optimization techniques to improve signal quality.

Contribution

It introduces a novel joint beamforming optimization framework for IRS-assisted radar, addressing nonconvex problems with SDR and demonstrating improved radar performance.

Findings

IRSs create effective LOS paths, improving target detection.

Joint optimization enhances radar robustness against blockage.

Simulation confirms significant performance gains.

Abstract

Intelligent reflecting surface (IRS) is a promising technology being considered for future wireless communications due to its ability to control signal propagation. This paper considers the joint active and passive beamforming problem for an IRS-assisted radar, where multiple IRSs are deployed to assist the surveillance of multiple targets in cluttered environments. Specifically, we aim to maximize the minimum target illumination power at multiple target locations by jointly optimizing the active beamformer at the radar transmitter and the passive phase-shift matrices at the IRSs, subject to an upperbound on the clutter power at each clutter scatterer. The resulting optimization problem is nonconvex and solved with a sequential optimization procedure along with semedefinite relaxation (SDR). Simulation results show that IRSs can help create effective line-of-sight (LOS) paths and thus substantially improve the radar robustness against target blockage.