Evaluation of the effect of satellite motion on GNSS-R wind speed retrieval: insights from TRITON

Evaluation of the effect of satellite motion on GNSS-R wind speed retrieval: insights from TRITON

TRITON is a newly launched GNSS-Reflectometry (GNSS-R) satellite mission by Taiwan, designed to enhance global sea surface wind monitoring. Among its scientific objectives, TRITON delivers high-resolution Delay Doppler Map (DDM) observations that enable novel investigations into the physical mechani...

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Bibliographic Details
Main Authors: Ming-Yi Chen, Hwa Chien, Wen-Hao Yeh, Li-Ching Lin, Yu-Fu Liou
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Remote Sensing
Subjects:
GNSS reflectometry
delay Doppler map
satellite relative velocity in bistatic mode
wind speed retrieval
deep learning
TRITON satellite
Online Access:https://www.frontiersin.org/articles/10.3389/frsen.2025.1657576/full
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Summary:TRITON is a newly launched GNSS-Reflectometry (GNSS-R) satellite mission by Taiwan, designed to enhance global sea surface wind monitoring. Among its scientific objectives, TRITON delivers high-resolution Delay Doppler Map (DDM) observations that enable novel investigations into the physical mechanisms shaping GNSS-R signal structures. In this study, we highlight the critical yet often overlooked role of transmitter–receiver relative velocity (Vrel) in influencing DDM morphology within the bistatic measurement geometry. Traditional geophysical model function (GMF) retrieval methods, which rely primarily on surface scattering assumptions, often neglect this orbital dynamic factor. Leveraging a deep learning-based framework, we empirically demonstrate that unaccounted-for Vrel can introduce systematic misinterpretations of surface roughness, likely due to DDM distortion. By explicitly incorporating Vrel as an input feature, our retrieval model achieves improved wind speed estimation accuracy from TRITON data, reducing root-mean-square error (RMSE) by over 11%. These results underscore the importance of orbital dynamics in GNSS-R applications and position TRITON as a valuable platform for advancing ocean remote sensing capabilities.
ISSN:2673-6187

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