Planning Model and Model Solve Method of Multi-base Multi -UAV Cooperative Reconnaiance

Abstract

Abstract: A UAV cooperative reconnaiance planning model with multi-base, multi-UAV, restrictions of target reconnaiance thime windows and target reconnaiance equipment was set up, and the model solve method was proposed. The take-off bases of the UAvs, the type of reconnaiance equipment carried and the target sequences reconnaianced by the UAVs were optimized in company in order to find the reconnaiance plan that need minimum number of UAVs. The process of signal plan forming was devided into two steps, the formation of the initial plan and the formation of the specific plan. The plans were ranked by the primary and secondary key words. The optimazation method based GA was proposed. According to the computationl experiments, high-quality reconnaiance plan can be worked out.

Key words: multi-base, multi-UAV, coopertive reconnaiance, time windows, Genetic Algorithm

CLC Number:

TP391.9

Li Yuan, Zhang Hui, Wu Sijin. Planning Model and Model Solve Method of Multi-base Multi -UAV Cooperative Reconnaiance[J]. Journal of System Simulation, 2016, 28(10): 2540-2545.

References 9

[1]	Ryan J L, Bailey T G, Moore J T, et al.Reactive tabu search in unmanned aerial reconnaissance simulation[C]// Proceedings of Winter Simulation Conference. USA: WSC, 1998: 873-879.
[2]	Hutchison M G.A method for estimating range requirements of tactical reconnaissance UAVs[C]// Proceedings of AIAA’s 1st Technical Conference and Workshop on Unmanned Aerospace Vehicles. Virginia, USA: AIAA, 2002:1-12.
[3]	Ousingsawat J, Mark E C.Establishing trajectories for muti-Vehicle reconnaissance[C]// Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit. Rhode Island, USA: AIAA, 2004:1-12.
[4]	Tian J, Shen L C, Zheng Y X.Formulation and a MOGA based approach for multi-UAV cooperative reconnaissance Design[J]. Visualization, and Engineering, International Conference on Cooperative Design (S0302-9743), 2006, 4101:99-106.
[5]	袁利平, 夏洁, 陈宗基. 多无人机协同路径规划研究综述[J]. 飞行力学, 2009, 27(5): 1-5.
[6]	吴文超, 黄长强, 宋磊, 等. 不确定环境下的多无人机协同搜索航路规划[J]. 兵工学报, 2011, 32(11): 1337-1342.
[7]	田菁, 沈林成. 多基地多无人机协同侦察问题研究[J]. 航空学报, 2007, 28(4): 913-914.
[8]	孙健, 刘慧霞, 席庆彪. 基于改进粒子群算法的多UVA协同侦察任务规划[J]. 现代电子技术 2012, 35(7): 12-15.
[9]	叶嫒嫒, 闵春平. 多无人机协同航路规划的共同进化方法[J]. 计算机仿真, 2007, 24(5): 37-39.

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