Joint Active and Passive Beamforming for IRS-Assisted Radar

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.

Cited by in corpus (5)

• The Rise of Intelligent Reflecting Surfaces in Integrated Sensing and Communications Paradigms
• Deep-Learning Channel Estimation for IRS-Assisted Integrated Sensing and Communication System
• Joint Beamforming for RIS-Assisted Integrated Sensing and Communication Systems
• Extreme Learning Machine-based Channel Estimation in IRS-Assisted Multi-User ISAC System
• Robust Transmission Design for RIS-Assisted Integrated Sensing and Communication Systems