Average and maximum revisit time trade studies for satellite constellations using a multiobjective Genetic Algorithm

Recently, versions of the Genetic Algorithm (GA) have successfully generated low-Earth orbit sparse coverage satellite constellations that appear to outperform traditionally developed constellations. The objective of these constellations was to minimize the maximum revisit time over a latitude band of interest. However, many constellation designers are also concerned with the average revisit time, and contrary to expectations, these two objectives often compete with each other. This paper presents a multiobjective GA approach to generate numerous constellation designs that show the trade-off between the revisit time objectives. These trade studies are conducted using a single run of the multiobjective GA. The designs generated using this approach are discussed and some trends are examined.