【摘要】 为了实现低空范围内的航线规划,首先通过转换坐标系,将多元问题转换为求各个航迹点纵坐标的单元问题,然后在综合考虑航迹段长度和威胁环境的约束条件下,通过建立两个约束条件的数学模型,最终确立头脑风暴算法(BSO)的目标函数,进而求取最优解,实现低空范围内的航线规划。在此基础上对传统头脑风暴算法进行改进,用密度聚类(DBscan)算法替代了k均值聚类(k-means)算法。仿真实验证明,改进后的算法较传统算法寻优能力更强,最终得到的航迹段更短,更适用于航线规划。更多还原

【Abstract】 In order to realize air route planning in low-altitude range,the multi-element problem is transformed into the single-element one of finding the ordinate of each flight track point by transforming the coordinate system. In consideration of the constraints of the flight track segment length and the threat environment comprehensively,the object function of brain storm optimization(BSO)algorithm is established by building the mathematical models of two constraints,so as to find the optimal solution and realize the air route planning in low-altitude range. On this basis,the traditional BSO algorithm is improved by replacing the K-means clustering algorithm with the density clustering(DBscan)algorithm. The simulation results show that in comparison with the traditional algorithm,the improved algorithm has stronger optimizing ability and shorter flight track segment length,which is more applicable to air route planning.更多还原