Characterizing Effective System Architectures for Cislunar Space Situational Awareness

Achieving Space Situational Awareness (SSA) in the Cislunar region—the area between the geosynchronous belt and the Moon's gravitational boundary—poses significant technological and organizational challenges. Instead of proposing new theoretical systems, this thesis employs the Architecting Innovative Enterprise Strategy (ARIES) Framework to evaluate existing SSA architectures and previously suggested solutions. ARIES provides a structured assessment through its elements (strategy, information, infrastructure, products, services, processes, organizations, and knowledge), identifying infrastructure, acquisition strategies, policy-driven timelines, and communication structures as key areas for improvement. Stakeholder objectives, current initiatives, and operational needs guide the characterization of an ideal SSA architecture. Four prior system proposals for cislunar SSA are assessed using qualitative analysis of existing literature and first-order physics-based simulations. These evaluations correlate specific design features with enhanced system suitability. Particularly beneficial are constellation proximity to targets, strategic constellation placement and phasing, sensor orbital diversity, and orbital stability. Additionally, certain design strategies consistently yield higher suitability, including focusing on underserved SSA regions, leveraging heritage technology, and optimizing designs for ride-share launch compatibility.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Institute for Data, Systems, and Society

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Rude, Connor D.

Advisor dc:contributor.advisor

• Rhodes, Donna H.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/162417

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/162417