地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (5): 948-957.doi: 10.12082/dqxxkx.2021.200303

• 遥感科学与应用技术 • 上一篇    下一篇

基于野外台站无人机组网遥感仿真航迹规划

李芹1(), 刘旭林1, 李荣昊1, 冯朝晖1, 李子锦1, 赵红颖1,2,*()   

  1. 1.北京大学 地球与空间科学学院 遥感与地理信息系统研究所,北京 100871
    2.北京大学 空间信息集成与3S工程应用北京市重点实验室,北京 100871
  • 收稿日期:2020-06-14 修回日期:2020-10-26 出版日期:2021-05-25 发布日期:2021-07-25
  • 通讯作者: 赵红颖
  • 作者简介:李 芹(1994— ),女,河北沧州人,硕士生,主要从事无人机组网任务规划研究。E-mail:1801210268@pku.edu.cn
  • 基金资助:
    国家重点研发计划项目(2017YFB0503003)

UAV Networking Remote Sensing Simulation Track Planning based on Field Station

LI Qin1(), LIU Xulin1, LI Ronghao1, FENG Zhaohui1, LI Zijin1, ZHAO Hongying1,2,*()   

  1. 1. Institute of Remote Sensing and Geographic Information System, School of Earth and Space Science, Peking University, Beijing 100871, China
    2. Beijing Key Laboratory of Spatial Information Integration and 3S Application, Peking University, Beijing 100871, China
  • Received:2020-06-14 Revised:2020-10-26 Online:2021-05-25 Published:2021-07-25
  • Contact: ZHAO Hongying
  • Supported by:
    National Key Research and Development Program of China(2017YFB0503003)

摘要:

无人机因其灵活、高分辨率等特点在遥感领域中得到了广泛应用,但是目前的无人机遥感多为单机作业,存在缺乏组网协同规划、作业效率有待提高等问题。无人机组网遥感观测能够克服单机作业存在的问题,可以实现多尺度、多平台、多载荷的高频次迅捷组网观测,快速获取大范围的超高分辨率数据,为大范围的生态环境监测、洪涝灾害监测以及国土安全应急监测提供数据支撑。无人机航迹规划能够为高频迅捷的无人机组网观测提供最优航迹。本文针对日益繁杂的航空遥感任务,以及无人机野外台站资源的逐渐完善,提出了基于野外台站的无人机遥感航迹规划模型,以优化后的单机航迹为基础,以无人机数量最少为目标进行多机组网任务分配,旨在解决基于台站的无人机组网航迹规划问题。首先对单机航迹进行优化,将无人机总航程分为有效作业航程和非有效作业航程,通过分析单机作业的任务约束,证明了非有效作业航程最短时作业效率最高,非有效作业航程由转弯航程以及无人机往返于台站的航程决定,因此,确定提高单机作业效率的航迹优化方法:采用“最小宽度”的方法确定最优飞行方向以减少转弯航程,以无人机往返于台站航程最短为原则确定最优的任务起点;其次,以优化后的单机航迹为基础,提出基于台站的无人机组网任务分配算法,考虑每架无人机往返于台站的航程,充分利用无人机的续航能力,以无人机数量最少为目标进行任务分配,从而获得基于台站的无人机组网航迹规化结果。通过仿真分析,验证了本文模型的有效性和正确性。

关键词: 野外台站, 遥感, 单机航迹优化, 遥感任务约束, 飞行方向选择, 任务起点选择, 任务分配, 无人机组网航迹规划

Abstract:

Unmanned Aerial Vehicles (UAVs) have been widely used in the field of remote sensing, due to the its flexibility and high resolution. However, the current remote sensing applications of UAVs are dominated by single UAV operations. There is still a lack of collaborative planning of UAV networking and the operation efficiency also needs to be improved. The UAV networking remote sensing can overcome these problems and provide high-frequency, multi-scale, multi-platform, and multi-load networking observations. The timely large-scale ultra-high-resolution data provided by the UAV networking remote sensing allow for large-scale ecological environment monitoring, flood disaster monitoring, and emergency monitoring of homeland security. Moreover, the UAV track planning can provide an optimal trajectory for high-frequency remote sensing observations. Thus, the research on UAV remote sensing track planning is of great significance. Given the increasing complex aerial tasks of remote sensing and increasing field station resources, a UAV networking remote sensing track planning model based on field stations is proposed in which the task assignment of the multi-unit network is carried out based on the optimized track planning of single UAV. Firstly, the optimization of track for a single UAV is carried out. The total flight of the drone is divided into effective flight and ineffective flight. By analyzing the remote sensing task constraints of a single UAV proves, we find that there is the highest efficiency when the ineffective flight is the shortest. The ineffective flight is determined by the turning flight and the flight of the UAV to and from the station. Therefore, the track optimization method to improve the efficiency of a single UAV is determined by reducing the turning distance and the distance that UAV to and from the station. The optimal flight direction is determined by the "minimum width" and the optimal mission starting point is determined by the principle that the flight of UAV to and from the station is the shortest. Secondly, based on the optimized track planning of a single UAV, a station-based task assignment algorithm for UAV networking is proposed. This algorithm takes into account the flight of each UAV to and from the station and takes full advantage of all flight. The task assignment is finally carried out by obtaining the track planning of UAV networking with the least number of UAVs. The feasibility of the model is verified by simulation examples in this study.

Key words: field station, remote sensing, single track planning optimization, remote sensing task constraint, flight direction selection, task starting point selection, task assignment, network track planning of UAV