Abstract：To improve the accuracy and reliability of the unmanned aerial vehicle (UAV)'s optimal path selection, a new optimal path selection method based on interval gray scale is proposed under the environment of uncertain flight surroundings and unknown security threat information. This paper established a new evaluating scale-interval gray, it is containing interval number and grey number. In which, the interval number is used to describe the uncertainty existing in the evaluation process, and the grey number is applied to describe the quantity of information. A reliability index of decision result is defined simultaneously. Then, UAV's path planning optimal selection method is proposed based on interval grey scale. A comparative simulation between the method proposed in this paper and interval decision method is given. The results show that the method proposed in this paper not only can improve the dispersion of evaluation index between the optimal alternatives and the subprime or the worst alternatives effectively, and reduce the degree of hesitation for decision-maker, but also can provide the reliability information for decision-making results, to increase the decision confidence.
[1] 王俊,周树道,朱国涛,等.无人机航迹规划常用算法[J].火力与指挥控制, 2012, 37(8):5-7. Wang J, Zhou S D, Zhu G T, et al. Research of common route planning algorithms for unmanned air vehicle[J]. Fire Control and Command Control, 2012, 37(8):5-7. [2] 李璠.无人机航迹规划算法研究[D].大连:大连理工大学, 2011. Li F. Unmanned aerial vehicle (UAV) route planning algorithm research[D]. Dalian:Dalian University of Technology, 2011. [3] Miao Y F, Zhong L X, Luo S. Application of improved sparse A* algorithm in UAV path planning[J]. Information Technology Journal, 2013, 12(17):4058-4062. [4] 刘莉,于成龙,王祝,等.小型无人机快速三维航迹规划方法[J]. 系统工程与电子技术, 2013, 35(12):2521-2526.Liu L, Yu C L, Wang Z, et al. Fast 3D route planning method for small UAV[J]. Systems Engineering and Electronics, 2013, 35(12):2521-2526. [5] Babak F M, Rubén R, Seyed J S. Vehicle routing problem with uncertain demands:An advanced particle swarm algorithm[J]. Computers Industrial Engineering, 2011, 62(1):306-317. [6] Roberge V, Tarbouchi M, Labonte G. Comparison of parallel genetic algorithm and particle swarm optimization for real-time UAV path planning[J]. IEEE Transactions on Industrial Informatics, 2013, 9(1):132-141. [7] 胡中华.基于智能优化算法的无人机航迹规划若干关键技术研究[D].南京:南京航空航天大学, 2011.Hu Z H. Research on some key techniques of UAV path planning based on intelligent optimization algorithm[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2011. [8] Cekmez U, Ozsiginan M, Sahingoz O K. A UAV path planning with parallel ACO algorithm on CUDA platform[C]//2014 International Conference on Unmanned Aircraft Systems, 2014:347-354. [9] 刘洋,章卫国,李广文,等.一种三维环境中的无人机多路径规划方法[J].西北工业大学学报, 2014, 6(3):412-416.Liu Y, Zhang W G, Li G W, et al. A multi-path planning method for Unmanned aerial vehicle (UAV) in 3D environment[J]. Journal of Northwestern Polytechnical University, 2014, 6(3):412-416. [10] Han D H, Kim Y D, Lee J Y. Multiple-criterion shortest path algorithms for global path planning of unmanned combat vehicles[J]. Computers and Industrial Engineering, 2014, 71(1):57-69. [11] Ferariu L, Cimpanu C. Multi objective hybrid evolutionary path planning with adaptive parieto ranking of variable-length chromosomes[C]//IEEE 12th International Symposium on Applied Machine Intelligence and Informatics, Proceedings, 2014:23-28. [12] 周伟杰,党耀国,熊萍萍,等.区间灰数的灰色变权与定权聚类模型[J].系统工程理论与实践, 2013, 33(10):2590-2595.Zhou W J, Dang Y G, Xiong P P, et al. Grey clustering model for interval grey number with variable and fixed weights[J]. Systems Engineering——Theory & Practice, 2013, 33(10):2590-2595. [13] 邓维斌,许昌林, 樊自甫.基于Vague集相似度量的多准则模糊决策方法[J].系统工程理论与实践, 2014, 34(4):981-990.Deng W B, Xu C L, Fan Z F. Multi-criteria fuzzy decision making method based on similarity measures between vague sets[J]. Systems Engineering——Theory & Practice, 2014, 34(4):981-990. [14] 李鹏,吴君民,朱建军.基于新直觉模糊距离的随机决策方法[J].系统工程理论与实践, 2014, 34(6):1517-1524.Li P, Wu J M, Zhu J J. Stochastic multi-criteria decision-making methods based on new intuitionists fuzzy distance[J]. Systems Engineering——Theory & Practice, 2014, 34(6):1517-1524. [15] 殷春武.模糊多准则群决策方法研究[D].西安:西安理工大学, 2007.Yin C W. Fuzzy multiple criteria group decision making method research[D]. Xi'an:Xi'an University of Science and Technology, 2007. [16] 徐泽水,达庆利.区间数排序的可能度法及其应用[J].系统工程学报, 2003, 18(1):67-70.Xu Z S, Da Q L. The possibility of interval number sequence method and its application[J]. Journal of Systems Engineering, 2003, 18(1):67-70.
2016, Vol. 36 
