Optimal Placement Method of Netted MIMO Radar Nodes Based on Hybrid Integration for Surveillance Applications

This paper is aimed to address the node placement problem in netted multiple-input multiple-output (MIMO) radar systems, aiming to elevate surveillance performance. Currently, most placement optimization strategies either focus on long- baseline netted MIMO radar systems under incoherent signal integration processing or just address short- baseline netted MIMO systems where signals are fused through coherent integration. These methods are not comprehensive for generalized netted MIMO radar systems encompassing mixed baselines. Therefore, we propose a signal processing architecture based on hybrid integration and, upon this, devise a multi-constraint mathematical optimization problem model targeted at optimizing node locations to further enhance surveillance performance. Within this problem, we fully consider constraints such as the number of system nodes, architecture, deployment area, and sparsity requirements to ensure the satisfaction of the system's finite resource requirements. Recognizing that the formulated optimization problem is nonconvex and complex, we introduce a metaheuristic method based on a two-stage search strategy to solve it. Through numerical experiments, we demonstrate the efficacy of our proposed node placement optimization solution. The results highlight its capability to significantly enhance surveillance performance by maximizing detection capabilities across different areas of varying importance, all while maintaining flexibility in resource allocation.