无人机群协同搜索航路规划仿真  

The Route Planning Simulation of UAV Cluster Cooperative Search

作　　者：韩旭 盛怀洁[1] 袁西超[1] HAN Xu;SHENG Huai-jie;YUAN Xi-chao(Electronic Engineering Institute of PLA,Hefei Anhui 230037,China)

机构地区：[1]解放军电子工程学院,安徽合肥230037

出　　处：《计算机仿真》2018年第9期37-41,共5页Computer Simulation

摘　　要：无人机群航路规划是实现无人机群对目标协同搜索的关键,为了解决航路规划中的协同航路选择问题,减小对航路进行寻优的计算量,提出了一种基于离散粒子群算法的搜索航路寻优方法。首先建立了无人机运动模型和探测模型,其次利用D-S证据理论的不确定性描述能力,建立了基于置信区间的搜索图,最后对自适应权重的粒子群算法进行了离散化改进,解决了无人机群搜索航路的优化选择问题。通过仿真及对比实验,验证了基于离散粒子群算法的协同搜索航路规划的高效性。The route planning is the key to achieve the UAV cluster cooperative goal searching. To deal with the problem of the selection of cooperative search path in route planning, a new method of search path optimizing based on discrete particle swarm Optimization is put forward and the amount of calculation for the search path is reduced. First of all, the UAV-motion model and the passive radar seeker detection model were established. Secondly, the search model for the operation area took the advantage of uncertainty description ability of D-S evidence theory. The search map was established based on confidence interval. To deal with the problem of search path optimizing, the a- daptive weight particle swarm optimization （AWPSO） was improved through discretization. According to the simulations and contrast tests, the high-efficiency of cooperative search based on the discrete particle swarm optimization was proved.

关 键 词：无人机群 协同搜索 搜索算法 离散粒子群算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]