SOSHA – Sensor Optimization for Space Habitat Awareness

Deep space habitats must provide a functional, hospitable, and safe environment with and without crew onboard. This will require Earth independent operation during periods of intermittent crew occupancy and reduced mission control support due to communication delays and data bandwidth limits. NASA needs advanced systems engineering tools to develop and operate integrated autonomous fault management (FM) capabilities. Sensor network (SN) design and tools for FM systems verification and validation (V&V) are critical gaps. The optimal combination, density, and placement of sensors for fault detection and diagnosis and communicating spacecraft state in complex, dynamic, integrated subsystems may be difficult to ascertain from a large SN design space. Model-based systems engineering (MBSE) tools can help to reduce design space complexity, facilitate sensor suite optimization (SSO), and evaluate FM system performance, thus improving the safety, effectiveness, and cost of autonomous FM system development. Space Lab, in collaboration with the University of Colorado at Boulder, proposes the Sensor Optimization for Space Habitat Awareness (SOSHA™), an MBSE tool to support the design, verification, and validation of sensor networks and algorithms employed by smart habitat FM systems. SOSHA will be a major step towards autonomous systems development for Earth-independent spacecraft operation. The design is also readily transferable to terrestrial applications, including the management of industrial internets of things (IIoT) for industrial process monitoring. The Phase I project goal is to demonstrate SOSHA proof of concept. Objectives are to 1) Demonstrate critical functions in an autonomous SSO process; 2) Investigate feasibility of non-critical, low TRL SOSHA functions; and 3) Plan for V&V of high-fidelity SOSHA prototype. Through conceptual design, breadboard prototype demonstration, and high-fidelity V&V planning, the proposed project will raise SOSHA TRL from 2 to 4.