中文摘要：

在无人机航迹规划中，通过改变惯性权重和采用自适应粒子群编码方式，以最大转弯半径、步进、最短距离和回避威胁作为航迹的评价指标，将约束条件、地形地貌及威胁信息引入适应度函数等方法，对粒子群优化算法进行改进，解决了粒子群算法在寻优过程中易陷入局部最优的问题．仿真结果表明，该方法可实现在线实时航迹规划．

英文摘要：

Aim to route planning for UAV, the particle swarm optimization algorithm was improved by changing in- ertia weight and using selbadaption coding means, the maximum horizontal swerving angle,maximum climbing/gli- ding angle,minimum flight-path step, minimum flight height, and the shortest flight-path distance are taken as evalu ation indexes of the adaptability functiom The constraint condition and the general configuration of the earth＇s sur face and threaten information was imported to the function of adaption, It used to solve the problem that PSO easily falls into a local the extremum. The simulation results show that this method can meet the online route planning.