基于气象威胁的无人机航迹规划方法研究  

Route Planning of UAVs Based on Weather Threat

作　　者：朱国涛[1,2] 周树道[1] 吕波[2] 王彦杰[1] 王俊[1] 

机构地区：[1]解放军理工大学气象学院 [2]中国人民解放军94195部队

出　　处：《电光与控制》2011年第6期26-30,共5页Electronics Optics & Control

摘　　要：针对复杂气象条件下的无人机航迹寻优问题,用栅格法进行环境建模;在基本蚁群算法的基础上,用确定性选择与随机性选择相结合的方法对节点的状态转移规则进行改进。用精英蚂蚁系统、最大最小蚂蚁系统及最好最差蚂蚁系统思想更新信息素规则,对部分参数进行自适应处理,并将遗传操作融入航迹搜索过程中,同时对航迹进行平滑处理。仿真结果表明,改进的蚁群算法具有较强的航迹搜索能力,较好地克服了基本蚁群算法早熟及陷入局部最优等缺点,通过规避风险及禁飞区,找到适合无人机飞行的最优解或近似最优解。How to find optimal solutions in route planning of UAVs under adverse weather was studied.Grid method was applied to establish an environment model.The conversion rule of node state was improved by combining decided selection with random selection.The pheromone updating rule was improved through Elitist Ant System（ASe）,Max-Min Ant System（MMAS） and Best-Worst Ant System（BWAS） on the basis of traditional Ant Colony Algorithm（ACA）.Some parameters were processed adaptively.Genetic operations were used to generate the routes,which were smoothed to optimize the routes.Simulation results show that the Improved ACA has strong ability in routes searching,which can overcome the shortcomings of the traditional ACA and may find the optimal or approximate optimal solution suitable for UAV.

关 键 词：无人机 航迹规划 气象威胁 蚁群算法 遗传算法 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计] TP391.9[自动化与计算机技术—计算机应用技术]