False Alarm Suppression for Clutter in ISAC Systems

Abstract

Urban low-altitude sensing is a critical application scenario for the Integrated Sensing and Communication (ISAC) system. However, detecting low-altitude, slow-moving and small (LSS) targets such as unmanned aerial vehicles (UAVs) in complex urban environments faces great challenges. In particular, multipath effects and ground moving object (GMO) clutter result in high false alarm rates. Conventional clutter suppression algorithms and existing sensing models are insufficient to support high-confidence sensing for the ISAC system. To address this issue, this paper introduces a novel target verification layer between the target detection layer and the target recognition layer, and proposes a new sensing signal model that decouples reflection characteristics from channel characteristics by constructing a dedicated Reflection Characteristic Function (RCF), which enables targeted discrimination of clutter-induced false alarms. Guided by the established model, a verification beam-based method for clutter false alarm suppression is proposed to address low-altitude ghost targets caused by vehicles. Simulation results show significant performance improvement in suppressing strong ground-dynamic clutter from vehicles.