Beamforming Design of Dual Intelligent Reflecting Surface Aided ISAC System Based on Cramér-Rao Bound Optimization

This paper investigates the design of joint transmit and reflective beamforming for dual intelligent reflecting surfaces (IRSs) aided integrated sensing and communication (ISAC) system. We aim to minimize the Cramér-Rao bound (CRB) for the direction of arrival (DOA) estimation of a target in the non-line-of-sight (NLOS) scenario while satisfying the per-user signal-to-interference-plus-noise ratio (SINR) constraints. One IRS is used to support NLOS sensing and communication functions simultaneously, while the other only assists the communication function of the system. Considering that the optimization problem is non-convex, we adopt semidefinite relaxation (SDR) and successive convex approximation (SCA) methods to iteratively solve the transmit beamformers and the reflection coefficients of two IRSs in the framework of alternating optimization. Simulation results indicate that the proposed scheme is more effective than the benchmark scheme.