From the Earth to the Moon: A Multi-Domain Approach to Cislunar Space Domain Awareness

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Date

2025-06-03

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Publisher

Virginia Tech

Abstract

Growing interest in the Cislunar domain has resulted in numerous successful Lunar missions in recent years. Many burgeoning space programs, including those by governments and private industry, have seized the opportunity of this renewed interest and utilized the region as a proving ground to bring relevance and credibility to their organizations. With this increase in interest and activity, the need to expand Space Domain Awareness (SDA) into the Cislunar regime has become paramount. This dissertation presents two related studies operating in different domains that address the current challenges faced by accomplishing this task. The first study optimizes future satellite constellation configurations of optical sensors placed on periodic orbits within the Circular Restricted Three-Body Problem (CR3BP) through the development of a novel multivariate normal crossover technique for Genetic Algorithms that enables statistical local and global search of discrete populations. With this strategy, the entire JPL Cislunar Three-Body Periodic Orbit Catalog's 272,008 unique periodic orbits are explored to produce sets of Pareto optimal solutions that demonstrate the most effective combinations of periodic orbit families for maintaining SDA of Cislunar space. The second study employs a currently operational ground-based electro-optical sensor network to search a pared-down area representing the intersection of low-thrust maneuvers from periodic orbits in the CR3BP and a spherical Poincaré map at four times the distance of Geosynchronous Earth Orbit (GEO). The results from this study demonstrate the feasibility of employing currently operational sensors to perform Cislunar SDA through an 85.3% decrease in the required search area in addition to the ability to conduct partial Cislunar SDA through search of the current GEO catalog with no operational changes.

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Keywords

Genetic Algorithm, Crossover, Optimal Constellation Design, Ground-Based Electro-Optical Search, GEO

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