As launch capabilities and interest in Cislunar missions expand for commercial, government, and military actors alike, so grows the necessity for a robust architecture in the Cislunar region for conducting Space Domain Awareness (SDA). Among the numerous objectives associated with constructing a robust Cislunar SDA architecture, of particular interest is creating an architecture that is cost effective for both architecture users and maintainers. This paper builds on previous work of using reinforcement learning methods to solve the multi-objective Cislunar architecture design problem by modeling a cooperative architecture user that seeks to maximize detectability by the architecture while minimizing total delta-v needed to do so. We also introduce a novel clustering method by which architectures explored during optimization are be grouped together, allowing us to better understand how observers must work in concert to produce optimal results. Through the interactions between the cooperative agent and architectures, we can further our understanding of the architecture design process while gaining insights into the fundamental qualities of a robust Cislunar architecture.
Cislunar Space Domain Awareness Architecture Design and Analysis for Cooperative Agents
J Astronaut Sci
2024-10-01
Article (Journal)
Electronic Resource
English
Cislunar Space Domain Awareness Architecture Design and Analysis for Cooperative Agents
Springer Verlag | 2024
|Capacity-based Cislunar Space Domain Awareness Architecture Optimization
British Library Conference Proceedings | 2022
|Observability Metrics for Space-Based Cislunar Domain Awareness
Springer Verlag | 2023
|