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Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China

In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the mo...

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Autores principales: Qi, Zhanhui, Li, Shaowu, Li, Mingbing, Dang, Chaoqun, Sun, Dongbo, Zhang, Dongliang, Liu, Ning, Zhang, Suoping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387341/
https://www.ncbi.nlm.nih.gov/pubmed/30696045
http://dx.doi.org/10.3390/s19030541
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author Qi, Zhanhui
Li, Shaowu
Li, Mingbing
Dang, Chaoqun
Sun, Dongbo
Zhang, Dongliang
Liu, Ning
Zhang, Suoping
author_facet Qi, Zhanhui
Li, Shaowu
Li, Mingbing
Dang, Chaoqun
Sun, Dongbo
Zhang, Dongliang
Liu, Ning
Zhang, Suoping
author_sort Qi, Zhanhui
collection PubMed
description In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the movement velocity of the buoy using the Doppler frequency shift of satellite GPS signals, and then to calculate the wave parameters from the movement velocity according to ocean wave theory. The shortage of the GPS wave buoy is the occasional occurrence of some unusual values in the movement velocity. This is mainly due to the fact that the GPS antenna is occasionally covered by sea water and cannot normally receive high-quality satellite GPS signals. The traditional solution is to remove these unusual movement velocity values from the records, which requires furthering extend the acquisition time of satellite GPS signals to ensure there is a large enough quantity of effective movement velocity values. Based on the traditional GPS wave measurement technology, this paper presents the algorithmic flow and proposes two improvement measures. On the one hand, the neural network algorithm is used to correct the unusual movement velocity data so that extending the acquisition time of satellite GPS signals is not necessary and battery power is saved. On the other hand, the Gaussian low-pass filter is used to correct the raw directional wave spectrum, which can further eliminate the influence of noise spectrum energy and improve the measurement accuracy. The on-site sea test of the SBF7-1A GPS wave buoy, developed by the National Ocean Technology Center in China, and the gravity-acceleration-type DWR-MKIII Waverider buoy are highlighted in this article. The wave data acquired by the two buoys are analyzed and processed. It can be seen from the processed results that the ocean wave parameters from the two kinds of wave buoys, such as wave height, wave period, wave direction, wave frequency spectrum, and directional wave spectrum, are in good consistency, indicating that the SBF7-1A GPS wave buoy is comparable to the traditional gravity-acceleration-type wave buoy in terms of its accuracy. Therefore, the feasibility and validity of the two improvement measures proposed in this paper are confirmed.
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spelling pubmed-63873412019-02-26 Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China Qi, Zhanhui Li, Shaowu Li, Mingbing Dang, Chaoqun Sun, Dongbo Zhang, Dongliang Liu, Ning Zhang, Suoping Sensors (Basel) Article In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the movement velocity of the buoy using the Doppler frequency shift of satellite GPS signals, and then to calculate the wave parameters from the movement velocity according to ocean wave theory. The shortage of the GPS wave buoy is the occasional occurrence of some unusual values in the movement velocity. This is mainly due to the fact that the GPS antenna is occasionally covered by sea water and cannot normally receive high-quality satellite GPS signals. The traditional solution is to remove these unusual movement velocity values from the records, which requires furthering extend the acquisition time of satellite GPS signals to ensure there is a large enough quantity of effective movement velocity values. Based on the traditional GPS wave measurement technology, this paper presents the algorithmic flow and proposes two improvement measures. On the one hand, the neural network algorithm is used to correct the unusual movement velocity data so that extending the acquisition time of satellite GPS signals is not necessary and battery power is saved. On the other hand, the Gaussian low-pass filter is used to correct the raw directional wave spectrum, which can further eliminate the influence of noise spectrum energy and improve the measurement accuracy. The on-site sea test of the SBF7-1A GPS wave buoy, developed by the National Ocean Technology Center in China, and the gravity-acceleration-type DWR-MKIII Waverider buoy are highlighted in this article. The wave data acquired by the two buoys are analyzed and processed. It can be seen from the processed results that the ocean wave parameters from the two kinds of wave buoys, such as wave height, wave period, wave direction, wave frequency spectrum, and directional wave spectrum, are in good consistency, indicating that the SBF7-1A GPS wave buoy is comparable to the traditional gravity-acceleration-type wave buoy in terms of its accuracy. Therefore, the feasibility and validity of the two improvement measures proposed in this paper are confirmed. MDPI 2019-01-28 /pmc/articles/PMC6387341/ /pubmed/30696045 http://dx.doi.org/10.3390/s19030541 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Qi, Zhanhui
Li, Shaowu
Li, Mingbing
Dang, Chaoqun
Sun, Dongbo
Zhang, Dongliang
Liu, Ning
Zhang, Suoping
Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China
title Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China
title_full Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China
title_fullStr Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China
title_full_unstemmed Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China
title_short Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China
title_sort research on the algorithm model for measuring ocean waves based on satellite gps signals in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387341/
https://www.ncbi.nlm.nih.gov/pubmed/30696045
http://dx.doi.org/10.3390/s19030541
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