A physical cluster-based passive scatterer detection method in ISAC systems

This paper proposes a novel passive scatterer detection method in integrated sensing and communication (ISAC) systems. The proposed scatterer detection method employs Subspace Alternating Generalized Expectation maximization (SAGE) to estimate the parameters of the multipath components (MPCs), which are used to determine the locations of scattering points (SPs). Subsequently, a joint clustering and tracking algorithm is applied to identify the clusters which the SPs belong to. As a result, valuable information of scatterer is obtained, including location, quantity and shape. The proposed method leverages the relationship between physical clusters and scatterers in the environment, which is validated according to channel simulation based on ray-tracer. Compared to other scatterer detection methods, the proposed approach can detect scatterers with high accuracy, low false alarm rate and miss alarm rate, and low mean center distance error with real-time detection capability.