以巡航导弹航迹规划为应用背景,提出了一种基于Voronoi图与改进遗传算法的巡航导弹分层航迹规划算法。该算法基于Voronoi图建立威胁模型对规划环境进行描述,生成初始航迹及导航点;采用变长度染色体整数编码方式,基于回溯深度优先算法产生初始种群,并设计了相应的遗传算子。进行了仿真试验,通过与遗传算法规划结果进行对比,验证了该方法在巡航导弹航迹规划快速性与最优性方面的提高。

A cruise missile hierarchical path planning algorithm was put forward based on Voronoi diagram and improved genetic algorithm (IGA) for application of the cruise missile path planning. The algorithm establishes the threat model based on Voronoi diagram to describe the planning environment and generate the initial paths and navigation nodes. It involves variable length chromosome integer encoding, takes advantage of backtracking depth priority algorithm to generate the initial population, and appropriate genetic operators were designed. Then the simulation experiment was conducted, and the result was compared with genetic algorithm (GA), this method can improve the speed and optimality of cruise missile path planning.