On-Orbit Demonstration of Surface Feature-Based Navigation and Timing

This NASA-UT Austin cooperative agreement matured a Machine Learning (ML) surface-feature recognition Position, Navigation, and Timing (PNT) technology for use in lunar orbit. As applied to the lunar environment, the technology allows for estimating spacecraft state and time bias relative to a reference solution using optical tracking of lunar craters for spacecraft in the 100’s-1000’s km lunar orbital range. During the two-year USTP project, the effort accomplished the development of a Crater-based Navigation and Timing (CNT) software module that consisted of the tested crater detection and neural network software suite. All components of the CNT software were integrated and tested using both simulated detections and sample Lunar Reconnaissance Orbiter (LRO) images. With simulated detections and various levels of fidelity, both the position estimation and time bias estimation utilities satisfy existing performance metrics of a maximum error of 100 m per position axis and 100 ms accuracy in time for spacecraft in the 100’s to 1000’s km lunar orbital regimes. In addition, the team developed a concept for a LEO on-orbit CubeSat demonstration that uses the same software, albeit with coastal features instead of lunar ones for PNT estimates.

A notable technology gap is the lack of availability of cost-effective PNT technologies for spacecraft in the 100’s to 1000’s km lunar orbits that are independent of the Deep Space Network (DSN), an already over-subscribed asset. This technology directly addresses that gap using an ML-based software module and cost-effective CubeSat-compatible sensor suite (visible and infrared cameras), to achieve 100 meters per axis and 100 milliseconds accuracy for lunar orbits in the 100’s-1000’s km. This makes for highly beneficial PNT technology for CubeSats that can easily be ported cost-effectively to much bigger spacecraft. In addition, the team has been funded for LEO on-orbit CubeSat demonstration – to be launch by end of 2026 – that will not only validate the system in orbit, but potentially provide a cost-effective solution too for use in LEO.

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