Aiming at the problems of unreasonable search range and low optimization performance in meteorological drone trajectory planning under complex obstacle threat environments, as well as the shortcomings of sometimes low and unstable optimization accuracy of the basic Jaya algorithm and easy to fall into local optima, a meteorological drone trajectory planning method based on multi-strategy improvement Jaya algorithm optimization is proposed. In order to meet the practical applications, the performance index trajectory planning model based on the weight coefficient method with the spherical coordinate system is established using the shortest trajectory, the minimum threat, the flight altitude, and the flight angle as the performance indexes, as well as the obstacles as the constraints. The simulation results of the improved algorithm for its solution are given, and the performance is compared with other heuristic algorithms. The results show that the planned path can be safer and more effective in avoiding hazardous sources by comprehensively considering the performance of the meteorological drone. Compared with other algorithms, the improved algorithm performs well in terms of searching accuracy and stability and generates the higher-quality trajectory.

中文翻译：

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用于气象无人机轨迹规划的混合进化Jaya算法


针对复杂障碍物威胁环境下气象无人机轨迹规划搜索范围不合理、优化性能低的问题，以及基础Jaya算法有时优化精度低且不稳定、易陷入局部最优的缺点，提出了一种气象无人机轨迹规划算法。提出了基于多策略改进Jaya算法优化的无人机轨迹规划方法。为了满足实际应用，以最短轨迹、最小威胁、飞行高度、飞行角度为性能指标，建立球坐标系下基于权重系数法的性能指标轨迹规划模型，如下以及作为限制的障碍。给出了改进算法对其求解的仿真结果，并与其他启发式算法进行了性能比较。结果表明，综合考虑气象无人机的性能，规划的路径能够更安全、更有效地避开危险源。与其他算法相比，改进算法在搜索精度和稳定性方面表现良好，生成的轨迹质量更高。