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Optimizing coverage and revisit time in sparse military satellite constellations a comparison of traditional approaches and genetic algorithms

机译:优化稀疏军事卫星群的覆盖范围和重访时间,比较传统方法和遗传算法

摘要

Sparse military satellite constellations were designed using two methods: a traditional approach and a genetic algorithm. One of the traditional constellation designs was the Discoverer II space based radar. Discoverer II was an 8 plane, 24 satellite, Low Earth Orbit (LEO), Walker constellation designed to provide high-range resolution ground moving target indication (HRR-GMTI), synthetic aperture radar (SAR) imaging and high resolution digital terrain mapping. The traditional method designed 9-ball, 12-ball, 18-ball, and 24- ball Walker constellations. The genetic algorithm created constellations by deriving a phenotype from a triploid genotype encoding of orbital elements. The performance of both design methods were compared using a computer simulation. The fitness of each constellation was calculated using maximum gap time, maximum revisit time, and percent coverage. The goal was to determine if one design method would consistently outperform the other. The genetic algorithm offered a fitness improvement over traditional constellation design methods in all cases except the 24-ball constellation where it demonstrated comparable results. The genetic algorithm improvement over the traditional constellations increased as the number of satellites per constellation decreased. A derived equation related revisit time to the number of ship tracks maintained.
机译:使用两种方法设计了稀疏的军用卫星星座:传统方法和遗传算法。传统星座设计之一是Discoverer II天基雷达。 Discoverer II是8飞机,24卫星,低地球轨道(LEO),Walker星座,旨在提供高分辨率的地面移动目标指示(HRR-GMTI),合成孔径雷达(SAR)成像和高分辨率的数字地形图。传统方法设计了9球,12球,18球和24球的Walker星座。遗传算法通过从编码轨道元素的三倍体基因型推导表型来创建星座。使用计算机仿真比较了两种设计方法的性能。使用最大间隔时间,最大重访时间和覆盖百分比来计算每个星座的适应性。目的是确定一种设计方法是否将始终优于另一种设计方法。遗传算法在所有情况下都比传统星座设计方法具有更好的适应性,但在24球星座上却表现出可比的结果。随着每个星座图卫星数量的减少,遗传算法对传统星座图的改进也随之增加。导出的方程将重访时间与所维护的航迹数量相关。

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    Parish Jason A.;

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  • 年度 2004
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