Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features

Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features

The accuracy of geophysical retrievals from radiometers relies on calibration quality, encompassing both absolute radiometric accuracy and spectral consistency. Radiometers have employed various calibration techniques, including external targets, vicarious sources, and internal calibrators like nois...

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Bibliographic Details
Main Authors: Ahmed Manavi Alam, Mehmet Kurum, Mehmet Ogut, Ali C. Gurbuz
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Calibration
deep learning (DL)
machine learning
microwave radiometry
neural network
radio frequency interference (RFI)
Online Access:https://ieeexplore.ieee.org/document/10318952/

Internet

https://ieeexplore.ieee.org/document/10318952/

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