基于弹道下降方式的无人机风险评估与航路规划

针对无人机系统失效后对地面人员及财产安全的威胁，提出了一种基于弹道下降方式下的无人机风险评估及航路规划方法。分析了无人机失效后的下降特点及规律，采用栅格法划分空域环境，以地面不同属性构建低空空域环境风险评估模型。结合无人机飞行的风险值、路径长度和空域情况，建立了多目标、多约束的无人机飞行航路规划模型。利用改进蚁群算法进行求解：优化转移概率，避免蚂蚁陷入死区间和减少盲目搜索；对信息素的更新进行改进，调整自适应系数增强最优路径的信息素浓度，提高算法收敛速度与稳定性。相比传统蚁群算法的路径规划，运行时间缩短6.7%、最优路径风险值降低41.45%、整体性能提高18.0%。仿真结果表明：本文模型及改进算法可以在提高路径安全性的前提下，缩短规划路径生成时间且保障运行的经济性。

UAV risk assessment and route planning based on ballistic descent method

In order to address the threat to the safety of ground personnel and property after UAS failure, a risk assessment and route planning method for UAVs based on ballistic descent method is proposed. The descent characteristics and laws of UAV after failure are analyzed, the raster method is used to divide the airspace environment, and the risk assessment model of low-altitude airspace environment is constructed with different attributes on the ground. Combine the risk value, path length and airspace of the UAV flight, a multi-objective and multi-constrained UAV flight path planning model is established. Solving with improved ant colony algorithm: optimize the transfer probability to avoid ants falling into dead intervals and reduce blind search; improve the update of pheromone, adjust the adaptive coefficient to enhance the pheromone concentration of the optimal path, and improve the convergence speed and stability of the algorithm. Compared with the path planning of the traditional ant colony algorithm, the running time is shortened by 6.7%, the risk value of the optimal path is reduced by 41.45%, and the overall performance is improved by 18.0%.The simulation results show that the model and the improved algorithm can shorten the planning path generation time and ensure the economy of operation while improving the path safety.