【摘要】 编队无人机对目标无人机进行围捕是多无人机战场作战中重要且典型的任务之一，本文将无线紫外光通信技术与围捕算法结合，提出了一种紫外光通信协作编队无人机联盟围捕算法。该算法借助无线紫外光辅助无人机编队机间数据保密传输和非直视通信，将联盟生成算法与区域最小化策略进行融合，采用动态规划法对最优联盟结构进行求解，使用区域最小化策略对目标无人机实施空中围捕，完成在复杂场景中无人机编队高效围捕多目标任务。对区域最小化策略和本文提出的紫外光协作编队无人机联盟围捕算法进行了仿真对比，实验结果表明：所提出的紫外光协作编队无人机联盟围捕算法在无人机编队围捕多目标过程中平均降低了12.73%的能耗，算法迭代次数平均降低了27.49%，验证了该算法能耗少、围捕效率高的性能。更多还原

【Abstract】 It is one of the most important and typical tasks for formation unmanned aerial vehicle(UAV) to round-up target UAV in multi-UAV battlefield operations. This study combines wireless ultraviolet(UV) communication technology with round-up algorithms and proposes a UV unmanned aerial vehicle alliance round-up algorithm collaborative formation. With the help of wireless UV assisted UAV formation, data confidentiality transmission, and nondirect-looking communication, the algorithm integrates alliance generation algorithm with the regional minimization strategy. The dynamic programming method is then used to solve the optimal alliance structure. Meanwhile, the area minimization strategy is employed to implement the target UAV aerial round-up, and the efficient UAV formation round-up multitarget task in complex scenarios is completed. The simulation comparison shows that the proposed UV collaborative formation UAV alliance round-up algorithm reduces both energy consumption by an average of 12. 73% in the UAV formation multitarget round-up process and algorithm iterations by 27. 49% than the regional minimization strategy. Therefore, this verifies the plausibility of algorithm performance with low energy consumption and high round-up efficiency.更多还原