High Rate Digital Spectrometer Enhancement with Neural Network AI
Description
As spaceborne spectrometer increases in spectral resolution, the growth in spectral data volume and the limited space to Earth communication bandwidth are prone to be a problem for achieving higher fidelity science measurement. To effectively utilize the limited communication bandwidth while reducing the loss of science data, a smart on-board neural network processing that had been successful in the field of machine learning and artificial intelligence (AI) is proposed to potentially reduce the spectral data volume, retaining the essential spectral information and mitigating the effect of human introduced radio signal interference.
Detailed example
Predictions
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
High Rate Digital Spectrometer Enhancement with Neural Network AI
Controls / human review
ATO: Not reported; PIA: Not published