Enhanced Heuristic Algorithm for Optimal Cislunar Space Situational Awareness Architecture

Document Type

Conference Proceeding

Publication Date

9-16-2024

Abstract

The goal of this study is to utilize heuristic optimization techniques, such as Genetic Algorithms, to examine near- optimal space-based sensor architectures within the cislunar environment for the space situational awareness (SSA) mission. Specifically, this study introduces an adapted heuristic algorithm for optimizing cislunar SSA architectures. The algorithm incorporates a categorical variable for selecting cislunar families’ periodic orbits, leading to shorter chromosome lengths and enhanced satellite capacity within a single family at reduced costs. Additionally, the algorithm allows for the removal of hidden genes, facilitating calculations for set-size architectures. Evaluation of the algorithm’s efficacy will be evaluated by assessing potential benefits such as reduced runtime and improved solution quality. The optimization problem will seek to analyze the trade-offs between SSA capability, station keeping costs, and number of satellites in a given constellation. These objectives are competing for resources within the optimization problem, so a Pareto front of optimal solutions depicting the cost of favoring a given objective will be provided. Trajectory maintenance requirements in terms of stability, as well as various satellite constellation designs utilizing different periodic orbit designs (e.g., Halo, Lyapunov, distant retrograde orbits) will be investigated to provide a baseline assessment of SSA functionality in the volume of space extending from geosynchronous Earth orbit to the Moon and beyond into translunar space. A “cloud of point” target deck will be employed covering the Earth-Moon corridor and the Earth-Moon L1, L2, L4, and L5 points. Visual magnitude SSA metric will be used to evaluate the detectability of the target deck by the architectures evaluated by the Genetic Algorithm, The research will use the circular-restricted three-body problem (CR3BP) as the foundational dynamical model. The research will comprise three fundamental components: (1) generation of a catalog of three-body periodic orbits in excess of 1,000 candidate trajectories; (2) analysis of SSA models and design criteria; and (3) formulation, simulation, and evaluation of SSA architectures comprising sensors in cislunar periodic orbits utilizing the aforementioned heuristic search algorithm.

Source Publication

2024 Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS)

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