Joint Multi-Target Matching and Parameter Estimation for Multi-BS Cooperative OFDM ISAC

Integrated sensing and communications (ISAC) in distributed networks presents an efficient solution for multi-target localization. This paper investigates the joint target matching and parameter estimation with multiple cooperative base stations (BSs), where each BS can only estimate the range and radial velocity of a subset of targets. The interdependence of these tasks introduces a mixed measurement-to-target association (MTA) problem, characterized by prohibitively significant computational complexity due to the binary constraints and the growing number of variables with an increasing number of targets and BSs. To address this challenge, we propose an iterative algorithm that alternates between target matching and parameter estimation, supported by a heuristic initialization method to enhance efficiency. Simulation results demonstrate the robustness of the proposed method, achieving high matching accuracy under different system configurations, including scenarios with low sensing resolution and an increasing number of targets.