Demonstrating Onboard Inference for Earth Science Applications with Spectral Analysis Algorithms and Deep Learning

TL;DR

This paper demonstrates onboard data analysis for Earth science using spectral algorithms and deep learning on a satellite, enabling real-time measurements and responses.

Contribution

It showcases the first practical implementation of onboard inference combining spectral analysis and neural networks on a hyperspectral satellite.

Findings

Successful onboard inference demonstration on CS-6 satellite

Enhanced real-time Earth science measurements possible

Integration of spectral analysis with deep learning hardware

Abstract

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.