ARADISS: Adaptive Real-Time Anomaly Detection & Identification For Space Systems

Space missions continue to increase in number, complexity, and time amp; cost constraints. To lead technological advancements and successfully execute these missions, NASA desires new amp; robust onboard automated fault management technologies that address the full range of hardware amp; software faults, are transparent amp; reusable across platforms. This will lead to reduced costs and improved autonomy, resilience, amp; mission quality especially in missions that cannot afford comprehensive fault management and have a higher mission risk tolerance.Global Technology Connection, Inc., (GTC) proposes to automate generation of ARADISS (Adaptive Real-time Anomaly Detection and Identification for Space Systems) models tuned to any given system. Feasibility of this framework was successfully demonstrated in Phase I on multi-rotor UAVs, electric propulsion testbed, and a preliminary CubeSat dataset. In Phase II, GTC plans to use a CubeSat platform used on NASA missions to steer the development, evaluation, and hardware integration planning. ARADISS models include simple machine learning norm models to estimate system operational variables, and self-adapting anomaly detection and identification models. ARADISS framework is applicable to virtually all electrically powered systems. Independent one-one norm maps make this approach extremely reusable, transparent and explainable. ARADISS models can be rapidly adapted to any platform and are ideal for space platforms with limited processing power. Applicable future space mission platforms include NISAR, SWOT, Dragonfly, and SPHEREx.GTC has received interest from several space technology firms, and has partnered with CubeSat OEM and a space systems integration for Phase II for rapid technology transition and space deployment in Phase III.Aggressive commercialization activities are being carried out for technology transition to NASA and other commercial space applications.