Communications of the ACM
IBM to Open-Source Space Junk Collision Avoidance
Researchers are collaborating on an open source project to determine and predict the orbits of aman-made space debris, in order to avoid collisions.
Credit: U.S. National Aeronautics and Space Administration
IBM and researchers at the University of Texas at Austin are collaborating on an open source project to determine and predict the orbits of anthropogenic space objects (ASOs)—man-made space debris—in order to avoid collisions.
Current methods for orbit prediction rely on physics-based models using location data on ASOs from terrestrial-based sensors, which tends to be imperfect.
The Space Situational Awareness project uses machine learning (ML)-generated models that learn when physical models incorrectly predict an ASO's future location.
The project employs data from the U.S. Strategic Command through the space-track.org website, with IBM hardware running physical models to anticipate the orbits of all ASOs in low earth orbit and train ML models on the physics model error.
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