Programming UAV swarm operational test based on mission reliability

基于任务可靠性的无人集群作战试验方案设计

¹ College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
² Laboratory of Digital Software for High-End Equipment, National University of Defense Technology, Changsha 410073, China
³ Laboratory of Parallel and Distributed Processing, National University of Defense Technology, Changsha 410073, China
⁴ Beijing Institute of Tracking and Telecommunications Technology, Beijing 100094, China

Received: 16 January 2024

Abstract

An UAV swarm is a promising new type of weapon. It is important to carry out its operation trials to check its combat effectiveness. Due to high cost and long time consumption, it is necessary to program the operation trials in advance and formulate efficient trial programs. This study aims to explore the programming of UAV swarm operation trials. To ensure the success of trials, an operation trial programming method based on mission reliability is proposed. The programming method first constructs a mission reliability model for UAV swarm operation trial missions such as reconnaissance, attack and reconnaissance attack. Then, using the multi-objective quantum particle swarm optimization algorithm, the Pareto boundary is solved and the optimal program that comprehensively considers reliability and cost is determined. Finally, a simulation case is used to verify the correctness of the proposed programming method, which is a useful exploration of UAV swarm operation trial programming.

摘要

无人机集群是具有前景的新质武器, 开展无人机集群作战试验是检验其作战效能的重要手段。由于成本高昂、耗时较长, 需要对作战试验提前规划, 制定高效的试验方案。为探讨无人机集群作战试验方案设计、保障试验的成功, 提出了基于作战试验任务可靠性的试验方案设计方法。该方法构建了无人机集群侦察任务、打击任务和侦察打击任务的作战区域任务可靠性模型, 使用多目标量子粒子群(multi-objective quantum particle swarm optimization algorithm, MOQPSO)方法求解出帕累托(Pareto)边界, 确定综合考虑可靠性和成本2个目标后的最优方案, 并通过仿真案例验证了所提方法的正确性。所提方法是解决无人机集群试验方案设计问题的有益探索。