An AI/ML approach to detection of launch and orbital debris in the upper atmosphere

We propose developing an AI/ML feature detection framework for detecting mesospheric aerosols, including plumes from rocket launches, to be initially applied to the Ozone Mapping Profiler Suite-Limb Profiler (OMPS-LP) dataset. The framework will be applicable and enhancing to upcoming NASA missions (e.g., the NASA Stratosphere Troposphere Response using Infrared Vertically-resolved light Explorer, STRIVE). The output dataset of mesospheric aerosol perturbations will be available for use in Earth system models to assess radiative and chemical impacts of these increasingly frequent events, as well as more generally to the research, defense, and intelligence communities to observe and study the impacts of upper atmospheric perturbations on radiation propagation relevant to communication and guidance systems.

AI/ML feature detection framework for mesospheric aerosols/rocket plumes using OMPS-LP; output dataset of mesospheric aerosol perturbations usable in Earth system models; assessment of radiative and chemical impacts of increasingly frequent launch events.

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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