协调联网无人飞行器进行持续区域拒止

Y. Liu, J. B. Cruz, A. Sparks
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引用次数: 36

摘要

研究了多联网无人机在执行持续区域拒止任务时的协同控制问题。采用自适应马尔可夫链模型预测弹出式威胁的位置。利用预测弹窗威胁和实际弹窗目标的混合信息,制定网络化无人机的协同策略。该方法通过使用多联网无人机的仿真试验台和蒙特卡罗仿真运行来评估我们的合作策略来说明。理论分析和仿真结果均证明了利用预测弹窗信息提高PAD整体任务性能的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coordinating networked uninhabited air vehicles for persistent area denial
This paper explores the problem of cooperative control among multiple networked unmanned air vehicles (UAVs) for persistent area denial (PAD) mission. An adaptive Markov chain model is used to predict the locations of pop-up threats. The mixed information of predicted pop-up threats and actual pop-up targets is utilized to develop cooperative strategies for networked UAVs. The approach is illustrated by use of a simulation test bed for multiple networked UAVs and Monte Carlo simulation runs to evaluate our cooperative strategy. Both theoretical analysis and simulation results are presented to demonstrate the effectiveness of using predicted pop-up information in improving the overall PAD mission performance.
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