Joint Path Planning and Time Resource Optimization for Simultaneous Search and Localization Tasks

To address the issues of low effective coverage rate during search operations, low precision in localization tasks, and single-task execution caused by predetermined flight paths in traditional UAV formations, this paper proposes an optimization method for path planning and time allocation that simultaneously achieves radar search functionality and multi-target joint localization tasks. Firstly, an effective surveillance rate is established based on the search requirements of the radar system, and the CRLB is used as the measurement accuracy indicator based on the target localization requirements. These two factors are then weighted to form the objective function to be optimized. Secondly, an optimization model is established based on kinematic constraints and time allocation constraints. Subsequently, the particle swarm algorithm is utilized to iteratively optimize the UAV’s path and time allocation frame by frame. Simulation results demonstrate that, compared to default path and time allocation, the proposed optimization scheme for path planning and time allocation offers superior overall performance in both search and measurement tasks.