Cooperative ISAC Systems With Extended Targets: Performance Analysis and Beamforming Design

This paper investigates a cooperative integrated sensing and communication (ISAC) system, where multiple base stations (BSs) employ coordinated transmit beamforming to communicate with their respective users and jointly sense a set of extended targets (ETs). Different from prior cooperative ISAC works considering point targets (PTs), the visible scatterers on the same extended target (ET) and the radar cross section (RCS) of the same scatterers observed by multiple BSs are considered to be different. Given the model, we first derive the Cramér-Rao bound (CRB) for the BSs to cooperatively estimate the ET’s parameters, thus quantifying the cooperative sensing gains. Next, based on the derived CRB, we formulate a joint node selection and coordinated transmit beamforming design problem with the object of minimizing the average trace of sensing CRB, while satisfying the minimum communication rate constraint, the maximum transmit power constraint, and the node selection constraints. To solve this non-convex optimization problem, we first utilize the block coordinate descent (BCD) method to decompose it into node selection sub-problem and beamforming design sub-problem. Next, the continuous relaxation and linear programming (LP) approach are employed to handle the node selection sub-problem, and a decentralized augmented Lagrangian manifold optimization algorithm is developed to solve the beamforming sub-problem with reduced computation complexity. Numerical simulations demonstrate that the proposed design outperforms benchmark designs with larger CRB-rate region. Moreover, our results show the impacts of the ET’s state and the number of network nodes on network performance to enable valuable ISAC beamforming design insights.