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Simulated annealing and genetic algorithm approaches for discontinuous coverage satellite constellation design

机译:不连续覆盖卫星星座设计的模拟退火和遗传算法方法

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摘要

Constellations of Earth orbiting satellites are used to perform many tasks. If the constellation's coverage need not be continuous in time, the number of satellites and, therefore, the cost of the constellation may be decreased. Finding constellations that minimize revisit times for discontinuous coverage is posed as an optimization problem. Practical limits on coverage analysis provide objective functions that are not differentiable, so non-gradient-based optimization methods are necessary. Simulated annealing and a genetic algorithm were applied to discontinuous coverage problems for various numbers of satellites and Earth central angles, providing both whole Earth and zonal coverage. Results are presented and compared to constellation designs from a traditional approach. Simulated annealing appears to provide answers with less computational effort, but the genetic algorithm is capable of simultaneously generating different designs with the same revisit times. Additional conclusions about these approaches for discontinuous coverage satellite constellation design are made.
机译:地球轨道卫星的星座用于执行许多任务。如果星座的覆盖范围不需要在时间上连续,则可以减少卫星的数量,从而降低星座的成本。寻找使不连续覆盖的重访时间最小化的星座是优化问题。覆盖率分析的实际限制提供了不可区分的目标功能,因此非基于梯度的优化方法是必要的。将模拟退火和遗传算法应用于各种数量的卫星和地球中心角的不连续覆盖问题,从而提供整个地球和纬向覆盖范围。呈现结果并将其与传统方法的星座设计进行比较。模拟退火似乎可以用较少的计算量来提供答案,但是遗传算法能够以相同的重访时间同时生成不同的设计。关于不连续覆盖卫星星座设计的这些方法的其他结论。

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