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

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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.

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Acknowledgements

This work has been funded by the Georgia Tech Research Institute (GTRI)’s Independent Research and Development (IRAD) program.

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  1. Lois Visonneau and Yuri Shimane have contributed equally to this work.

Authors and Affiliations

  1. Daniel Guggenheim School of Aerospace Engineering, Georgia Institute of Technology, 620 Cherry St NW, Atlanta, GA, 30332, USA

    Lois Visonneau, Yuri Shimane & Koki Ho

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  1. Lois Visonneau
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Correspondence to Koki Ho.

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Visonneau, L., Shimane, Y. & Ho, K. Optimizing Multi-spacecraft Cislunar Space Domain Awareness Systems via Hidden-Genes Genetic Algorithm. J Astronaut Sci 70, 22 (2023). https://doi.org/10.1007/s40295-023-00386-8

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