雷达威胁环境下的多无人机协同航迹规划

doi:10.3969/j.issn.0255-8297.2014.03.010

应用科学学报 ›› 2014, Vol. 32 ›› Issue (3): 287-292.doi: 10.3969/j.issn.0255-8297.2014.03.010

雷达威胁环境下的多无人机协同航迹规划

郜晨，甄子洋，龚华军

南京航空航天大学自动化学院，南京210016

收稿日期:2013-03-18 修回日期:2013-11-18 出版日期:2014-05-31 发布日期:2013-11-18
作者简介:甄子洋，副教授，研究方向：飞行控制、预见控制等，E-mail：zhenziyang@nuaa.edu.cn；龚华军，教授，博导，研究方向：先进飞行控制技术等，E-mail：ghj301@nuaa.edu.cn
基金资助:
国家自然科学基金(No.61304223)；高等学校博士学科点专项科研基金(No.20123218120015)；南京航空航天大学基本科研业务费专项科研基金(No.NS2013029, No.NN2012101)；南京航空航天大学研究生创新基地(实验室)开放基金(No.kfjj20130211); 中央高校基本科研业务费与专项资金资助

Collaborative Path-Planning of Multiple UAV in Radar Threatening Environment

GAO Chen, ZHEN Zi-yang, GONG Hua-jun

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received:2013-03-18 Revised:2013-11-18 Online:2014-05-31 Published:2013-11-18

摘要/Abstract

摘要： 针对雷达威胁环境下的多无人机协同航迹规划问题，提出一种基于Voronoi图与蚁群算法结合的智能规划方法. 根据雷达威胁分布建立赋权Voronoi 图，将连续可飞空域离散化为网格点. 通过选取适当的参数放宽蚁群算法的最优性，将每架无人机寻优得到的多组解作为多条备选航迹，建立以协同时间为约束的协同函数，根据协同时间最优决策方法选出每架无人机的最终飞行航迹，进行航迹平滑处理后得到实际可飞航迹. 仿真结果表明，所提出的智能航迹规划方法具有时间协同和整体最优等优点.

关键词: 多机协同, 航迹规划, Voronoi 图, 蚁群算法, 最优控制

Abstract: To solve the problem of collaborative path planning of multiple unmanned aerial vehicles (UAV) under radar threatening environment, an intelligent method based on Voronoi diagram and ant colony optimization (ACO) algorithm is proposed. According to known radar threat sources, a weighted Voronoi diagram
is created to discretize the flying space into a grid. ACO is then used to obtain a set of selectable paths for each UAV. The parameters are properly chosen to relax the optimality of ACO so that multi-solutions can be found. A coordination function is created, and the estimated team arrival time (ETA) is taken as the time constraint to pick out the final path of each UAV. The path is smoothed for actual flight. Simulation results show that the proposed method can satisfy the requirements of time coordination and overall optimal.

Key words: multiple UAV coordination, path planning, Voronoi diagram, ant colony optimization, optimization control

中图分类号:

V279

郜晨，甄子洋，龚华军. 雷达威胁环境下的多无人机协同航迹规划[J]. 应用科学学报, 2014, 32(3): 287-292.

GAO Chen, ZHEN Zi-yang, GONG Hua-jun. Collaborative Path-Planning of Multiple UAV in Radar Threatening Environment[J]. Journal of Applied Sciences, 2014, 32(3): 287-292.

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雷达威胁环境下的多无人机协同航迹规划

Collaborative Path-Planning of Multiple UAV in Radar Threatening Environment

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