Joint Beamforming Scheme for ISAC Systems via Robust Cramér-Rao Bound Optimization.

Integrated sensing and communication (ISAC) is a key technology in the new generation of wireless communication systems. The ability to ensure robust sensing performance for different targets becomes essential for ISAC systems. However, existing works have not been successful in guaranteeing this ability. In this letter, we propose a novel robust joint beamforming scheme to address this issue. Our approach formulates the robust joint beamforming problem as a min-max optimizer, aiming to minimize the maximum Cramér-Rao bound (CRB) of multi-target direction of arrival (DOA) estimation while ensuring the signal-to-interference-plus-noise ratio (SINR) of multi-user communication. The intractable min-max matrix diagonal element problem can be elegantly transformed into an eigenvalue optimization problem, which can be solved using a semidefinite relaxation (SDR) technique. Numerical results demonstrate that our proposed scheme can achieve robust multi-target DOA estimation for different targets, regardless of SINR thresholds and the number of communication users.