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A Computational Approach to Reduce the Revisit Time Using a Genetic Algorithm

机译:使用遗传算法减少重读时间的计算方法

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The genetic algorithms (GAs) have been recently used in many design problems including an orbit design and trajectory optimization problems due to their global search capability and the robust characteristics. Furthermore, the GAs do not require convenient analytical representations of the problem any more. For this reason, the GAs can provide good solutions to the orbital dynamics design problem, especially a local coverage problem of Low Earth Orbit (LEO), which is difficult to formulate and handle the problem since an orbit propagation and local coverage analysis should be performed at the same time. This paper presents the possibility to using a genetic algorithm as a computational approach to finding the temporary target orbit in order to reduce the average revisit time of current mission orbit over a particular target site during the specified days. Through a comprehensive simulation study, the possibility of using a genetic algorithm to apply this kind of a temporary reconnaissance mission using a single LEO spacecraft is successfully demonstrated.
机译:最近在许多设计问题中使用了遗传算法(气体),包括轨道设计和轨迹优化问题,因为它们的全球搜索能力和鲁棒特性。此外,气体不需要更多的问题的分析表示。因此,气体可以为轨道动力学设计问题提供良好的解决方案,尤其是低地球轨道(LEO)的本地覆盖问题,这很难制定和处理问题,因为应该执行轨道传播和本地覆盖分析同时。本文介绍了使用遗传算法作为查找临时目标轨道的计算方法,以减少特定日期在特定的目标网站上的当前任务轨道的平均重新访问时间。通过全面的仿真研究,成功地证明了使用遗传算法使用遗传算法应用这种临时侦察任务的应用。

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