Multi-target sensing based on cell-free ISAC systems: Architecture and Data Processing

With the advancement of integrated sensing and communication (ISAC), multi-target sensing and tracking in communication systems has emerged as a key application scenario. However, the limited angular resolution of single base station hinders high-precision sensing. To address this, cell-free technology offers a promising solution for distributed collaborative sensing. In this paper, we investigate the coop-erative hierarchy of cell-free ISAC networks and propose a novel architecture that supports functional partitioning be-tween distributed and central units. Specifically, an efficient multi-target tracking framework, named ISAC-SORT, is in-troduced, which utilizes a cascaded multi-target manager and specialized calibration-association algorithms to facilitate robust perception. Furthermore, an extended Kalman filter (EKF) is designed to fuse observation data from multiple nodes, enabling direct prediction and estimation of target positions based on range and Doppler measurements. Sim-ulation results demonstrate the framework’s robustness in dynamic scenarios involving temporary occlusions, sudden target emergence, and clutter interference, while maintaining decimeter-level precision even at low signal-to-noise ratios (SNRs). Finally, the fifth generation new radio (5G NR) standard-compliant outdoor experiments confirm that the system can achieve a sensing accuracy of 0.8 m.