无人机山区搜寻方法研究

发布时间：2018-02-26 20:36

  本文关键词： 无人机 山区 区域划分 路径规划 搜寻　出处：《中国民用航空飞行学院》2017年硕士论文　论文类型：学位论文

【摘要】：我国航空业正随着经济的发展而高速向前迈进,航空运输量逐步提升、航空企业逐渐增多、航空器数量迅速增长。航空业的蓬勃发展,也意味着航空安全将成为人们更加关注的焦点。航空器事故仍难以完全避免,高效的航空器搜寻方法将是减小航空器事故造成的生命财产损失和负面影响的重要途径。近年来,无人机行业飞速发展,无人机已经广泛应用于军事、农业、地质、气象等领域。将无人机应用于山区坠毁航空器搜寻中,它将具有成本低、受空间限制小、无人员伤亡风险等得天独厚的优势。结合上述的高效搜寻和无人机两个焦点与热点问题,本文进行了无人机山区搜寻方法研究。选取了适合进行山区搜寻的无人机;利用DEM数字高程模型与计算机技术生成了搜寻区域等高线障碍图;研究了无人机山区搜寻的航拍高度,并在航拍高度基础上,确立了搜寻高度层。参照直升机山区搜寻安全余度,结合山体坡度,确立了无人机山区搜寻安全余度,在此基础上,在等高线障碍物图中选取关键搜寻点,将关键搜寻点抽象为邻接矩阵,实现了无人机躲避山体所形成的障碍物,对邻接矩阵分别用遗传算法、模拟退火算法和蚁群算法计算出遍历所有关键搜寻点的最短路径,通过MATLAB的计算与仿真结果,对搜寻路径长度、算法稳定性、算法运行时间进行对比,得出适用于无人机山区搜寻路径规划的最优化算法。通过还原2008年汶川地震失事救援直升机的失事范围,理论结合实际地阐述了无人机山区搜寻方法。利用遥感技术,将搜寻区域分为山体表面、空旷山谷和障碍物繁多山谷。针对这三种不同的搜寻区域,分别制定了搜寻方案。通过遥感,对山区各搜寻高度层直径进行测量,确定山体表面搜寻方法。研究扇形搜寻、扩展方形搜寻数学模型,建立“∞”字搜寻数学模型,对比3种搜寻方式在相同范围内搜寻路径长度,得出最高效的无人机搜寻方式,确定空旷山谷搜寻方法。利用得出的无人机山区搜寻路径规划最优化算法,确定障碍物繁多山谷搜寻方法。
[Abstract]:With the development of economy, China's aviation industry is moving forward at a high speed. The volume of air traffic is gradually increasing, the number of aviation enterprises is increasing, and the number of aircraft is increasing rapidly. It also means that aviation safety will become the focus of more attention. Aircraft accidents are still difficult to avoid completely. Efficient aircraft search methods will be an important way to reduce the loss of life and property caused by aircraft accidents and the negative effects in recent years. With the rapid development of the UAV industry, UAVs have been widely used in military, agricultural, geological, meteorological and other fields. Combined with the above two focal points and hot issues of UAV, this paper studies the method of UAV mountain area search, and selects the UAV suitable for mountain search. The contour obstacle map of search area is generated by using DEM digital elevation model and computer technology, and the aerial altitude of UAV mountain area search is studied. The search height layer is established. The search safety redundancy of UAV mountain area is established by referring to the helicopter mountain area search safety margin and combining with the mountain slope. On this basis, the key search points are selected in the contour obstacle map. The key search points are abstracted as adjacency matrix, and the obstacle formed by UAV avoiding mountain is realized. The shortest path of traversing all the key search points is calculated by genetic algorithm, simulated annealing algorithm and ant colony algorithm respectively. Through the calculation and simulation results of MATLAB, the search path length, algorithm stability and algorithm running time are compared. The optimal algorithm for the route planning of UAV mountain area search is obtained. By reducing the crash scope of the rescue helicopter in Wenchuan earthquake on 2008, the method of unmanned aerial vehicle mountain area search is expounded theoretically and practically, and the remote sensing technology is used. The search area is divided into mountain surface, open valley and various obstacle valley. For these three different search areas, the search scheme is developed separately. The diameter of each searching height layer in mountain area is measured by remote sensing. The method of mountain surface search is determined, the fan search is studied, the mathematical model of square search is extended, the mathematical model of "鈭，

本文编号：1539629