【作者】 苏菲； 李远； 沈林成；

【Author】 SU Fei,LI Yuan,SHEN Lincheng College of Mechatronic Engineering and Automation,National University of Defense Technology,Changsha 410073

【机构】 国防科技大学机电工程与自动化学院；

【摘要】 采用蚁群算法对复杂战场环境中的UAV航迹规划问题进行研究。根据UAV所面临战场环境的特点,综合考虑航程和敌方威胁因素,设计了航迹综合代价评估方法。在基本蚁群算法的基础上,设计了UAV航迹规划蚁群算法对问题进行求解。针对复杂战场环境中UAV航迹规划问题特点,设计了基于综合航迹代价预估的状态转移规则,并结合自然界真实蚁群的行为特点,引入信息素扩散机制对算法进行改进,提高了算法的性能。仿真实验结果表明该方法能够有效地解决复杂战场环境中的UAV航迹规划问题。更多还原

【Abstract】 Ant colony algorithm is applied to solve UAV(Unmanned Aerial Vehicle) route planning in complex battle field environment.According to the properties of battlefield,an integrated cost estimate measure is presented,which takes the distance of UAV route and threats into account.Then a ant colony algorithm for UAV route planning is put forward to solve the problem.According to the characteristics of the UAV route planning in complex battlefield environment,state transition rules based on integrated cost estimation is designed,and the pheromone diffuse mechanism is introduced to improve the performance of algorithm.The simulation results demonstrate the feasibility and efficiency of our algorithm.更多还原