Demonstrating Onboard Inference for Earth Science Applications with Spectral Analysis Algorithms and Deep Learning
This work addresses the problem of enabling real-time Earth science measurements and responses for satellite missions by performing inference onboard, though it appears incremental as it focuses on demonstrating existing methods on new hardware.
The paper demonstrates onboard data analysis and inference for Earth science applications using deep learning and spectral analysis algorithms on the CogniSAT-6 satellite, enabling new measurements and responses by processing data at the edge.
In partnership with Ubotica Technologies, the Jet Propulsion Laboratory is demonstrating state-of-the-art data analysis onboard CogniSAT-6/HAMMER (CS-6). CS-6 is a satellite with a visible and near infrared range hyperspectral instrument and neural network acceleration hardware. Performing data analysis at the edge (e.g. onboard) can enable new Earth science measurements and responses. We will demonstrate data analysis and inference onboard CS-6 for numerous applications using deep learning and spectral analysis algorithms.