Abstract: To address the cooperative mission planning problem of multiple fixed-wing UAVs under non-uniform regional reconnaissance demands, conventional coverage path planning mainly focuses on geometric full-area coverage, while common task assignment methods emphasize platform-task resource allocation. These methods are difficult to directly characterize the matching relationship between the field-of-view statistics of imaging sensors and the regional demand distribution. Therefore, a field-of-view ergodic hierarchical cooperative reconnaissance mission planning method, termed FE-HCRMP, is proposed. For EO forward-looking imaging and SAR side-looking imaging, the proposed method constructs task-level average field-of-view statistical templates using sensor kernel functions and standard scanning centerlines, and establishes the field-of-view ergodic error through Fourier coefficients. Local strip reconnaissance tasks are generated under a fixed task-number constraint. Task assignment is then completed by considering UAV payload capability, task priority, transfer cost, and completion time. Finally, executable trajectories are generated according to fixed-wing motion constraints and sensor imaging geometry. Meanwhile, the equivalence of forward and reverse task execution in terms of task-level field-of-view statistics is analyzed, providing a basis for the hierarchical solution of task generation, task assignment, and trajectory planning. MATLAB simulation results show that the final ergodic error of FE-HCRMP is lower than those of the conventional CPP method and the demand-weighted CPP method, and the reconnaissance time in key regions is increased by about 50% compared with the conventional CPP method. The results indicate that the proposed method can make the field-of-view statistics of the UAV group closer to the non-uniform reconnaissance demand distribution while maintaining the feasibility of fixed-wing trajectories, showing better demand-matching capability and key-region resource focusing capability.

Key words: multi-UAV cooperative reconnaissance, fixed-wing UAV, field-of-view ergodic metric, imaging sensor, task generation, task assignment, trajectory planning