The Joint Resource Optimization Scheme for Phased Array Radar Networking in Unmanned Aerial Vehicle Swarm Combat Scenarios

This paper proposes a phased radar network power allocation optimization scheme for tracking unmanned aerial vehicle (UAV) swarms, which enables higher-precision tracking of UAV swarms under given resource budget. First, considering the characteristics of dense UAV quantities and spatial proximity, the scheme employs a Gaussian process-based three-dimensional extended target tracking method to model the swarm's spatial configuration. Second, based on the estimated shape and positional coordinates of the UAV swarm, a collaborative phased array radar network illumination strategy is formulated. Finally, the posterior Cramér-Rao lower bound (PCRLB) under the threedimensional framework is derived as a performance metric to construct and solve the optimization model. Simulation results demonstrate that the proposed scheme significantly enhances the tracking accuracy of networked radar systems for UAV swarms.