Optimizing Multi-spacecraft Cislunar Space Domain Awareness Systems via Hidden-Genes Genetic Algorithm

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Cislunar_SDA_HGGA.pdf (1.65 MB)
Author(s)
Visonneau, Lois
Shimane, Yuri
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Editor(s)
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Organizational Unit
Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
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Research Publications
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Permanent Link
https://hdl.handle.net/1853/75352
Abstract
This paper proposes an optimization problem formulation to tackle the challenges of cislunar Space Domain Awareness (SDA) through multi-spacecraft monitoring. Due to the large volume of interest as well as the richness of the dynamical environment, traditional design approaches for Earth-based architectures are known to have challenges in meeting design requirements for the cislunar SDA; thus, there is a growing need to have a multi-spacecraft system in cislunar orbits for SDA. The design of multi-spacecraft-based cislunar SDA architecture results in a complex multi-objective optimization problem, where parameters such as number of spacecraft, observability, and orbit stability must be taken into account simultaneously. Through the use of a multi-objective hidden genes genetic algorithm, this study explores the entirety of the design space associated with the cislunar SDA problem. A demonstration case study shows that our approach can provide architectures optimized for both cost and effectiveness.
Sponsor
GTRI IRAD
Date
2023-07-07
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Resource Type
Text
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Post-print
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