期刊名称：American Journal of Engineering and Technology Management
印刷版ISSN：2575-1948
电子版ISSN：2575-1441
出版年度：2017
卷号：2
期号：4
页码：36-44
DOI：10.11648/j.ajetm.20170204.11
语种：English
出版社：Science Publishing Group
摘要：Unmanned Aerial Vehicle (UAV) is a kind of new operational platform possessing ability to flight autonomously and perform independently a task,which can not only carry out non-attack tasks,such as military reconnaissance, surveillance and search, but also to carry out tasks to air-to-ground attacking, target bombing and so on. With the rapid development of UAVtechnology, more and more UAV will be applied in the future battlefield. An UAV combat troops have seven UAV bases, which are from P01 to P07. Every base has some FY-1 type UAVs. At the same time, FY-1 UAV can be loaded by two kinds of load, which are S-1 and S-2. Now we need to achieve the aim to detect 10 target groupsfromA01 to A10, which are total 68 goals. And each target group has radar station. Under the above condition, this papermakes the best plan for the UAV combat troops, and uses FY-1 UAV to find best route and scheduling strategy of UAV, which including each UAV drone off base, loading, departure time, track and target reconnaissance. The goal is to ensure minimum time summation in a effective probe range to stay defense radar for UAV. First of all, this paper considers only four UAV bases with FY-1 UAV, so the 68 targets are divided into four regions by K-means algorithm; Then the global shortest path model is established, when the local route is the shortest. The route is drawn according to the route. According to the former route, the general shortest path model is established. It is composed of shortest route distance and the distance from UAV to the corresponding area. And then this paper determine which base the UAV will go to. Finally, the minimum time is calculated as 17.52h. The eight UAVs are arranged in this process, which are composed of four UAVs withS-1 and fourUAVs withS-2. The UAVs are offered by P01, P03, P05 and P07.
关键词：Multi UAV Cooperative; Task Planning; K-Means Algorithm; Dynamic Time Window
