Aman Chandra, University of Arizona; Mostafa Lutfi, University of Arizona; David Gross, University of Arizona
Keywords: Model Based Systems Engineering, CubeSat, CubeSat Reference Model, Space Situational Awareness, Architecture driven, SSA reference model
Abstract:
Space Situational Awareness (SSA) is a needed strategic and security capability, whose importance directly correlates with the increases in utilization of near/low earth orbit, however the resources available for such are sharply limited. This has focused research on ways and means to improve the efficiency and effectiveness of proposed SSA infrastructure. SSA infrastructure broadly includes distributed and networked sensing, ranging and end effector systems, deployed over land, sea, in the atmosphere and in space. CubeSats, or standardized nano-satellite platforms, offer strong potential for meeting many of the requirements for SSA infrastructure and further CubeSats offer potentially significant reductions in cost, development time and failure risk over alternative infrastructure elements. For example, CubeSats may be rapidly and inexpensively deployed in controlled swarms, creating a space-based sensor network offering higher capability, flexibility, and robustness than other architectures.
Realizing this potential requires substantial systems analysis to determine the right configuration of individual CubeSats, other SSA infrastructure, and the networks that will actually enable an SSA system to accomplish its missions, however such work has traditionally required very large budgets and very long time lines. The present work discusses an initiative to reduce by orders of magnitude the budgets & timelines required for SSA systems analysis which is grounded in Model-Based Systems Engineering. In particular, this work examines leveraging a CubeSat Reference Model (CRM) within a SSA analysis framework. The CRM was developed by the International Council on Systems Engineerings (INCOSE) Space Systems Working Group and has been recently submitted to the Object Management Group (OMG) standardization process. The SSA systems analysis framework, developed in the Architecture Driven Systems lab at the University of Arizona, enables evaluation of a range of SSA architectures including human machine interactions in conjunction with automation across a range of generated scenarios as well as creation and evaluation of proposed SSA figures of merit. The work discusses suitability of the CRM for SSA systems analysis including validating existing features and suggesting refinements. It concludes by exploring the potential for a future SSA Reference Model.
Date of Conference: September 11-14, 2018
Track: Space-Based Assets