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Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction
Geocenter is the center of the mass of the Earth system including the solid Earth, ocean, and atmosphere. The time-varying characteristics of geocenter motion (GCM) reflect the redistribution of the Earth’s mass and the interaction between solid Earth and mass loading. Multi-channel singular spectru...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922311/ https://www.ncbi.nlm.nih.gov/pubmed/33671341 http://dx.doi.org/10.3390/s21041403 |
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author | Jin, Xin Liu, Xin Guo, Jinyun Shen, Yi |
author_facet | Jin, Xin Liu, Xin Guo, Jinyun Shen, Yi |
author_sort | Jin, Xin |
collection | PubMed |
description | Geocenter is the center of the mass of the Earth system including the solid Earth, ocean, and atmosphere. The time-varying characteristics of geocenter motion (GCM) reflect the redistribution of the Earth’s mass and the interaction between solid Earth and mass loading. Multi-channel singular spectrum analysis (MSSA) was introduced to analyze the GCM products determined from satellite laser ranging data released by the Center for Space Research through January 1993 to February 2017 for extracting the periods and the long-term trend of GCM. The results show that the GCM has obvious seasonal characteristics of the annual, semiannual, quasi-0.6-year, and quasi-1.5-year in the X, Y, and Z directions, the annual characteristics make great domination, and its amplitudes are 1.7, 2.8, and 4.4 mm, respectively. It also shows long-period terms of 6.09 years as well as the non-linear trends of 0.05, 0.04, and –0.10 mm/yr in the three directions, respectively. To obtain real-time GCM parameters, the MSSA method combining a linear model (LM) and autoregressive moving average model (ARMA) was applied to predict GCM for 2 years into the future. The precision of predictions made using the proposed model was evaluated by the root mean squared error (RMSE). The results show that the proposed method can effectively predict GCM parameters, and the prediction precision in the three directions is 1.53, 1.08, and 3.46 mm, respectively. |
format | Online Article Text |
id | pubmed-7922311 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79223112021-03-03 Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction Jin, Xin Liu, Xin Guo, Jinyun Shen, Yi Sensors (Basel) Article Geocenter is the center of the mass of the Earth system including the solid Earth, ocean, and atmosphere. The time-varying characteristics of geocenter motion (GCM) reflect the redistribution of the Earth’s mass and the interaction between solid Earth and mass loading. Multi-channel singular spectrum analysis (MSSA) was introduced to analyze the GCM products determined from satellite laser ranging data released by the Center for Space Research through January 1993 to February 2017 for extracting the periods and the long-term trend of GCM. The results show that the GCM has obvious seasonal characteristics of the annual, semiannual, quasi-0.6-year, and quasi-1.5-year in the X, Y, and Z directions, the annual characteristics make great domination, and its amplitudes are 1.7, 2.8, and 4.4 mm, respectively. It also shows long-period terms of 6.09 years as well as the non-linear trends of 0.05, 0.04, and –0.10 mm/yr in the three directions, respectively. To obtain real-time GCM parameters, the MSSA method combining a linear model (LM) and autoregressive moving average model (ARMA) was applied to predict GCM for 2 years into the future. The precision of predictions made using the proposed model was evaluated by the root mean squared error (RMSE). The results show that the proposed method can effectively predict GCM parameters, and the prediction precision in the three directions is 1.53, 1.08, and 3.46 mm, respectively. MDPI 2021-02-17 /pmc/articles/PMC7922311/ /pubmed/33671341 http://dx.doi.org/10.3390/s21041403 Text en © 2021 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 Jin, Xin Liu, Xin Guo, Jinyun Shen, Yi Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction |
title | Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction |
title_full | Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction |
title_fullStr | Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction |
title_full_unstemmed | Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction |
title_short | Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction |
title_sort | multi-channel singular spectrum analysis on geocenter motion and its precise prediction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922311/ https://www.ncbi.nlm.nih.gov/pubmed/33671341 http://dx.doi.org/10.3390/s21041403 |
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