Title:
Decision-Making and Optimization Framework for the Design of Emerging Satellite Constellations
Decision-Making and Optimization Framework for the Design of Emerging Satellite Constellations
Author(s)
Koerschner, Marc A.
Krishnan, Kavya Navaneetha
Payan, Alexia P.
Mavris, Dimitri N.
Krishnan, Kavya Navaneetha
Payan, Alexia P.
Mavris, Dimitri N.
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Abstract
With the parallel increase in global orbital debris due to passive object collisions, as well as in
the number of proposed low earth orbit mega-constellations, in anti-satellite missile tests, and the
fielding of new satellites, there is an inherent need for a framework to optimize the design of Low
Earth Orbit (LEO) mega-constellations to avoid collisions while maintaining the functionality of
the constellation. In this paper, we aim to provide a framework that unifies these considerations
in the conceptual design phase of mega-constellations. We start with a discussion of metrics
of importance for the design of mega-constellations, namely coverage, collision risk, collision
avoidance, and station-keeping costs. With these metrics defined, we utilize the first principles
of orbital mechanics and statistical models to analyze potential alternative mega-constellation
designs. These designs are then optimized using Non-denominated Sorting Genetic Algorithm
2 (NSGA2) with our own defined objective function to create a repository of Pareto optimal
configurations. We then showcase how a multi-criteria decision-making methodology can be
utilized by a variety of unique stakeholders and subject-matter experts to select an optimal
constellation design for a given scenario. A Pareto Frontier collection with optimal solutions
of 10 constellations was produced by the framework. Radar plots to assess the significance of
the weighted metric of the framework shows several trading options for conceptual designs of
the constellations. We finally discuss the scope, limitations, applications, and future work for
various scenarios.
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Date Issued
2023-01
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Paper