在研究无人机飞行管理过程中,受到广播式自动相关监视(ADS-B)技术监视航空目标的启示,设计了一种以ADS-B技术为基础的无人机航迹规划算法。将场势理论和ADS-B技术相结合,使该算法能够对无人机的飞行进行提前规划和管理。在随后的对比实验和仿真实验中,该文设计的算法在不同障碍数量下,航迹规划一次性成功率虽然略低于当前已有航迹规划算法,但是在规避风险和规划用时方面均优于Muga算法、Tmuga算法以及D15算法。在仿真实验中,该算法也成功地对无人机群在多种障碍下的航迹进行了规划。

The rapid development and large-scale application of drone technology, related management has gradually attracted the attention of the public and academic circles. In the course of flight management of aerial drone, inspired by ADS-B technology to monitor aviation targets, the field potential theory and ADS-B technology are combined to design a UAV track planning algorithm based on ADS-B technology, which can plan and manage the flight of uavers in advance. In the subsequent comparative experiments and simulation experiments, the algorithm designed in this paper, although the one-time success rate of track planning is slightly lower than that of the existing track planning algorithm, is better than the Muga algorithm, Tmuga algorithm, and D15 algorithm in terms of risk avoidance and planning time.

TN957. 52