面向多威胁的无人机智能目标跟随策略设计

祁晓明; 魏瑞轩; 周凯

doi:10.13700/j.bh.1001-5965.2015.0296

面向多威胁的无人机智能目标跟随策略设计

doi: 10.13700/j.bh.1001-5965.2015.0296

空军工程大学航空航天工程学院, 西安 710038

基金项目: 国家自然科学基金(61573373);航空科学基金(20135896027)

详细信息

作者简介:
祁晓明男,博士研究生。主要研究方向:多无人机协同搜索决策方法。 E-mail: fancyxiaoming@163.com;魏瑞轩男,博士，教授，博士生导师。主要研究方向:多无人机自主协同控制。 Tel.: 17082452676 E-mail: 2856402009@qq.com;周凯男,博士研究生。主要研究方向:多无人机协同控制方法。 E-mail: kaigemima@163.com

通讯作者:
魏瑞轩, Tel.: 17082452676 E-mail: 2856402009@qq.com

中图分类号: V1
计量
- 文章访问数: 883
- HTML全文浏览量: 50
- PDF下载量: 529
- 被引次数: 0
出版历程
- 收稿日期: 2015-05-11
- 修回日期: 2015-08-06
- 网络出版日期: 2016-04-20

Intelligent target following strategy design for UAV against multi-threats

Aerospace Engineering College, Air Force Engineering University, Xi'an 710038, China

Funds: National Natural Science Foundation of China(61573373);Aeronautical Science Foundation of China (20135896027)

摘要

摘要: 随着无人机(UAV)一体化作战的不断发展,无人机在搜索到运动目标之后,需要立即转入跟随模式,考虑到战场环境的复杂性,研究了在多个威胁源条件下无人机跟随运动目标的问题,为了保证无人机的安全性以及跟随目标的精确性,提出了一种基于决策树的无人机智能目标跟随策略。首先对威胁概率图(TPM)进行建模;然后采用几何图法及任务优先级生成不同的规则,建立相应的决策树,并设计了不同规则下无人机飞行航向及速度指令;最后通过仿真验证所提出的智能目标跟随策略的有效性。
- 威胁建模 /
- 无人机(UAV) /
- 梯度下降 /
- 规则 /
- 决策树 /
- 目标跟随 /
- 智能导航
Abstract: With the development of integrative combat, the task will be converted into target following mode when unmanned aerial vehicle (UAV) finishes searching ground moving target. Complex combat environment is considered, and the problem of UAV following moving target in the condition of multi-threats source are studied. An intelligent target following strategy based on decision trees is proposed in order to ensure the security of UAV and the precision of target following. Firstly, threat probability map (TPM) model was established. Secondly, the problem how to solve the minimum of TPM was researched. Then, the different rules were generated on the basis of the different priorities for object tasks by geometric method; the complete decision trees were established; the heading and speed commands of UAV were generated for different rules. Finally, simulation results demonstrate the validity of the proposed method.
- threat modeling /
- unmanned aerial vehicle (UAV) /
- gradient descent /
- rules /
- decision trees /
- target following /
- intelligent navigation

HTML全文

参考文献(17)

[1]	BERTUCCELLI L F, HOW J P.Search for dynamic targets with uncertain probability maps[C]//Proceedings of the 2006 American Control Conference.Piscataway,NJ:IEEE Press,2006:737-742.
[2]	ALTSHULER Y, YANOVSKY V,WAGNER I A,et al.Efficient cooperative search of smart targets using UAV swarms[J].Robotica,2008,26(4):551-557.
[3]	TRODDEN P, RICHARDS A.Multi-vehicle cooperative search using distributed model predictive control:AIAA-2008-7138[R].Reston:AIAA,2008.
[4]	CHOI J W, CURRY R E,ELKAIM G H.Real-time obstacle-avoidance path planning for mobile robots:AIAA-2010-8411[R].Reston:AIAA,2010.
[5]	王树磊,魏瑞轩, 沈东,等.面向航路规划的Laguerre图构造算法[J].系统工程与电子技术,2013,35(3):552-556. WANG S L,WEI R X,SHEN D,et al.Laguerre diagram construction algorithm for path planning[J].Systems Engineering and Electronics,2013,35(3):552-556(in Chinese).
[6]	MASEHIAN E, AMIN-NASERI M R.A Voronoi diagram visibility graph-potencial field compound algorithm for robot path planning[J].Journal of Robotic Systems,2004,21(6):275-300.
[7]	TOMONO M. Planning a path for finding targets under spatial uncertainties using a weighted Voronoi graph and visibility measure[C]//Proceedings of 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems.Piscataway,NJ:IEEE Press,2003:124-129.
[8]	CORTES J, MARTINEZ S,BULLO F.Robust rendezvous for mobile autonomous agents via proximity graphs in arbitrary dimensions[J].IEEE Transactions on Automatic Control,2006,51(8):1289-1298.
[9]	唐上钦,黄长强, 胡杰,等.基于威胁等效和改进PSO算法的UCAV实时航路规划方法[J].系统工程与电子技术,2010,32(8):1706-1710. TANG S Q,HUANG C Q,HU J,et al.Threat equivalent and improved PSO algorithm based real-time method of UCAV route planning[J].Systems Engineering and Electronics,2010,32(8): 1706-1710(in Chinese).
[10]	莫松,黄俊,郑征,等. 基于改进快速扩展随机树方法的隐身无人机突防航迹规划[J].控制理论与应用,2014,31(3): 375-385. MO S,HUANG J,ZHENG Z,et al.Stealh penetration path planning for stealth unmanned aerial vehicle based on improved rapidly-exploring-random-tree[J].Control Theory & Application,2014,31(3):375-385(in Chinese).
[11]	MUJUMDAR A, PADHI R.Evolving philosophies on autonomous obstacle and collision avoidance of unmanned aerial vehicles[J].Journal of Aerospace Computing Information and Communication,2011,8(2):17-41.
[12]	WANG X, YADAV V,BALAKRISHNAN S N.Cooperative UAV formation flying with obstacle/collision avoidance[J].IEEE Transactions on Control Systems Technology,2007,15(4): 672-679.
[13]	CALL B, BEARD R,TAYLOR C,et al.Obstacle avoidance for unmanned air vehicles using image feature tracking:AIAA-2006-6541[R].Reston:AIAA,2006.
[14]	FREW E, LAWRENCE D,MORRIS S.Coordinated standoff tracking of moving targets using Lyapunov guidance vector field[J].Journal of Guidance Control and Dynamics,2008,31(2):290-306.
[15]	RUANGWISET A. Path generation for ground target tracking of airplane-typed UAV[C]//Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics.Piscataway,NJ:IEEE Press,2009:1354-1358.
[16]	BELANGER J, DESBIENS A,GAGNON E.UAV guidance with respect of arrival specifications[C]//16th Mediterranean Conference on Control and Automation.Piscataway,NJ:IEEE Press,2008:1265-1270.
[17]	CHEN H, CHANG K C,AGATE C S.Tracking with UAV using tangent-plus-Lyapunov vector field guidance[C]//12th International Conference on Information Fusion,FUSION'09.Piscataway,NJ:IEEE Press,2009:363-372.