SBIR-STTR Award

Space missions continue to increase in number, complexity, and time & cost constraints. To lead technological advancements and successfully execute these missions, NASA desires new & robust onboard automated fault management technologies that address the full range of hardware & software faults, are transparent & reusable across platforms. This will lead to reduced costs and improved autonomy, resilience, & mission quality especially in missions that cannot afford comprehensive fault management and have a higher mission risk tolerance. Global Technology Connection, Inc., proposes ARADISS (Adaptive Real-time Anomaly Detection and Identification for Space Systems) framework applicable to virtually all electrically powered systems. It involves physics-guided machine learning models to detect and simultaneously locate faults. The feature learning ML models continue to learn in real-time to adapts to gradual system degradations which avoid extensive model training requirements. This technique has demonstrated comprehensive fault coverage with a high detection rate and a low detection latency in extensive tests on automobiles. Meaningful physical correlations to battery voltage fluctuations make this approach extremely transparent and immediately transferable to other platforms. These algorithms are computationally inexpensive to run and can be implemented on-board small space missions. In Phase I, we propose to validate this framework on a UAV and show feasibility demonstration and applicability to future space mission platforms like NISAR, SWOT, Dragonfly, and SPHEREx. In Phase II, our team will identify a space platform, tune, and test our algorithms in simulated environments for transition and space deployment in Phase III. Aggressive commercialization activities would be carried out throughout all phases of this program, and Phase III will concentrate on technology transition for NASA and other commercial space applications Potential NASA Applications (Limit 1500 characters, approximately 150 words): The US accounts for 74% of the global investment in space exploration. It is expected to grow to over $20B by 2027 from $14.6B in 2017. 63% of the planned 80 space missions over the next decade are government missions. NASA JPL mission types that could potentially benefit from automated fault management technology are spacecraft, rovers/landers, space instruments, space habitats, and ground systems. Specific applicable missions are NISAR, SWOT, SPHEREx, and future rovers/rotorcrafts. The algorithms can be implemented onboard these platforms Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words): Several US companies like Boeing, Lockheed Martin, Northrop Grumman, Raytheon, Space Systems, and SpaceX are active in the development of space technologies like spacecraft, satellites, & instruments and autonomous UAV systems. Our novel fault management technology will enable faster development, testing, and deployment timelines reducing the overall cost of missions. Duration: 6

Space missions continue to increase in number, complexity, and time & cost constraints. To lead technological advancements and successfully execute these missions, NASA desires new & robust onboard automated fault management technologies that address the full range of hardware & software faults, are transparent & reusable across platforms. This will lead to reduced costs and improved autonomy, resilience, & 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. Potential NASA Applications (Limit 1500 characters, approximately 150 words): The US accounts for 74% of the global investment in space exploration. It is expected to grow to over $20B by 2027 from $14.6B in 2017. 63% of the planned 80 space missions over the next decade are government missions. NASA JPL missions that could potentially benefit from automated fault management technology are satellites, spacecraft, rovers/landers, and space instruments. Specific applicable missions are Polaris, NISAR, SWOT, and SPHEREx. Our tools are ideal for onboard implementation. Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words): Several US companies like Lockheed Martin, Northrop Grumman, Planet Labs, SpaceX, and Argotec, Inc. are active in the development of spacecraft, satellites, & instruments, and UAV systems. Our novel fault management technology will enable faster development, testing, and deployment timelines, and also increase resilience. This will reduce the overall development, testing, and mission costs. Duration: 24