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Cloud-based near real-time sea level monitoring using GNSS reflectometry
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Cloud-based near real-time sea level monitoring using GNSS reflectometry
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Journal Article
Cloud-based near real-time sea level monitoring using GNSS reflectometry
2023
Overview
In addition to traditional tide gauges, the ground-based global navigation satellite system reflectometry (GNSS-R) that utilizes signal-to-noise ratio data from a single GNSS receiver has become another promising alternative for sea level monitoring. However, its application is limited by retrieval precision, especially in large tidal variation environments. On the other hand, previous studies have focused on performance improvement by using post-processing strategies, which cannot support practical (near-) real-time applications. In this work, we present a method using a robust Kalman filter to provide near real-time sea level measurements based on cloud service, achieving both high precision and high temporal resolution. A coastal GNSS station BRST with large tidal variations was selected for experimental validation. First, 30 days of archived GNSS observations were used for performance assessment. It is observed that high-precision sea level retrievals with a 5-min sampling interval can be obtained, which reaches a root-mean-square error of 5.87 cm and a correlation of 99.93% compared to the tide gauge records. Then, based on the Alibaba cloud service, we implemented a near real-time sea level monitoring system by using the real-time GNSS observations streamed by the International GNSS Service real-time service. It is shown that no detectable bias is found compared with the retrievals obtained in post-processing mode, which indicates that we can remotely sense sea level variations in near real-time and further promotes ground-based GNSS-R in practical sea level monitoring applications.
Publisher
Springer Nature B.V
