基于智能图搜索的滑翔式高超声速飞行器路径规划方法

Trajectory Planning of Hypersonic Gliding Vehicle Based on Smart Graph Search Method

研究了高超声速飞行器在线路径规划问题。首先建立滑翔式高超声速再入飞行器动力学模型,在此基础上综合考虑高超声速飞行器在飞行过程中的动压约束、热流约束、过载约束等,对动力学模型进行解析计算,分析再入走廊,并进一步分析形成滑翔式高超声速飞行器的覆盖区域。基于飞行器覆盖区域并结合工程应用需求,提出了速度分段的高超声速飞行器可达区域计算方法,以确定在不同终端速度约束下的高超声速飞行器可抵达区域。并以此为基础,以各个速度分段的终端速度为节点,提出了基于启发式路径搜索算法的分段路径规划方法,通过变步长图搜索算法可在飞行过程中在线确定各个速度分段区间的终点,完成分段路径搜索规划。最后通过数值仿真验证了所提路径规划方法的有效性,结果表明,该方法计算效率高,能够有效规划高超声速飞行器的机动飞行轨迹,具有一定的工程应用前景。

This paper aims to investigate the online path planning problem of hypersonic vehicles. This essay comprehensively studies the dynamic pressure constraints, heat flow constraints, and overload constraints of the hypersonic vehicles during their flights by establishing a dynamic model of the gliding hypersonic re-entry vehicles. To acquire the range of the re-entry corridor, the established dynamic model is analyzed so that the coverage area of the hypersonic vehicles can be further calculated. By taking both the coverage area of the air vehicles and the requirements of engineering applications into consideration, the calculation method of the velocity-segmented reachable area of the hypersonic vehicles is proposed in this paper to confirm the reachable area of the hypersonic vehicles under different terminal speed constraints. This study takes the terminal speed of each speed segment as the node, which is analyzed and calculated by the segmented path planning method(SPPM) based on the heuristic path search algorithm in this paper. What’s more, with the variable step size graph search algorithm, each speed segment interval can be confirmed online during the vehicles’ flights, at the same time, the segmented path searching can be planned and completed as well. The effectiveness of the SPPM which is based on the heuristic path search algorithm is successfully verified by the numerical simulation. The results show that this method has high computational efficiency and it can effectively plan the maneuvering flight trajectory of hypersonic vehicles. Last but not least, the results also reveal the potential of future applications in the engineering field of the SPPM based on the heuristic path search algorithm.