Passive Sensing in a Near-Field Multi-ISAC System With Imperfect CSI

Integrated Sensing and Communication (ISAC) is an emerging technology that enables simultaneous communication and radar sensing, thereby enhancing spectrum utilization. With advancements in extremely large-scale antenna arrays and tremendously high frequencies, the near-field region is expected to expand significantly. ISAC in the near-field region has become a key technology for the future of wireless communications. However, current research on near-field ISAC systems mainly focuses on a single ISAC base station (BS), which leads to limitations in sensing range and accuracy in parameter estimation. Additionally, the uncertainty in Channel State Information (CSI) can severely affect both communication and sensing performance, particularly in near-field environments. To address these challenges, we propose a novel near-field multi-ISAC passive sensing system with multiple transmitters and a dedicated receiver. To evaluate the limits of sensing performance, we first derive the Cramér-Rao Bound (CRB) as our performance metric. We then formulate a joint communication and sensing beamforming design problem aimed at minimizing the CRB while ensuring the required communication quality of service (QoS) and adhering to total power constraints. We further apply the Schur complement and the Semi-Definite Relaxation (SDR) technique to solve this complex problem. Moreover, we develop a robust Multiple Signal Classification (MUSIC) algorithm to estimate the location of targets within our multi-ISAC passive sensing system, even with imperfect CSI. To demonstrate the advantages of our proposed scheme, we compare it with an active sensing system and a beamforming approach. Simulation results confirm the robustness and effectiveness of the proposed passive sensing system, showcasing its collaborative capability to enhance sensing performance and alleviate the influence caused by the imperfect CSI.