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Vol. 34, No. 8(3), S&M3042

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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 31, Number 6(3) (2019)
Copyright(C) MYU K.K.
pp. 2167-2182
S&M1922 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2019.2252
Published: June 28, 2019

Detection of Diurnal and Semidiurnal Tidal Signatures from Continuous GPS Daily Vertical Residual Time Series by Frequency Mixing Method [PDF]

Yu Peng, Wen Chen, Danan Dong, Chao Yu, Zhiren Wang, Jun Yan, and Min Liu

(Received December 30, 2018; Accepted March 8, 2019)

Keywords: CGPS, diurnal and semidiurnal tidal signatures, tidal displacements, harmonic analysis, frequency mixing, time series

The diurnal and semidiurnal tidal displacements in the continuous GPS (CGPS) daily coordinate time series cannot be perfectly removed by ocean tide models, especially in coastal regions. The residual tidal displacements will propagate to the daily time series as alias signals with longer periods ranging from about 2 weeks to 1 year, which can be theoretically calculated. However, the alias signals with long periods (e.g., more than half a year) are difficult to detect through alias harmonic analysis when the length of the time series is insufficient. To extract all the diurnal and semidiurnal tidal displacements from the daily coordinate time series, we propose the frequency mixing method, that is, converting the signals from a high frequency to a low frequency, before the harmonic analysis. We demonstrate the feasibility of this method using simulated data and analyze the spectra of real daily vertical residual time series from eight globally distributed CGPS stations. The solar-related ocean tidal constituents (K1, P1, K2, and S2) are clearly detected from the time series by this method, verifying that the FES2004 model on solar-related ocean tidal displacement should be improved.

Corresponding author: Wen Chen


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Cite this article
Yu Peng, Wen Chen, Danan Dong, Chao Yu, Zhiren Wang, Jun Yan, and Min Liu, Detection of Diurnal and Semidiurnal Tidal Signatures from Continuous GPS Daily Vertical Residual Time Series by Frequency Mixing Method , Sens. Mater., Vol. 31, No. 6, 2019, p. 2167-2182.



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