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...
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doaj-da97861550e14c819f1f0f110c8eca5d2021-02-18T00:03:54ZengMDPI AGSensors1424-82202021-02-01211403140310.3390/s21041403Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise PredictionXin Jin0Xin Liu1Jinyun Guo2Yi Shen3College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaSchool of Geographic Sciences, Xinyang Normal University, Xinyang 464000, ChinaGeocenter 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.https://www.mdpi.com/1424-8220/21/4/1403multi-channel singular spectrum analysisgeocenter motionpredictionautoregressive moving average |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xin Jin Xin Liu Jinyun Guo Yi Shen |
spellingShingle |
Xin Jin Xin Liu Jinyun Guo Yi Shen Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction Sensors multi-channel singular spectrum analysis geocenter motion prediction autoregressive moving average |
author_facet |
Xin Jin Xin Liu Jinyun Guo Yi Shen |
author_sort |
Xin Jin |
title |
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_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_sort |
multi-channel singular spectrum analysis on geocenter motion and its precise prediction |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-02-01 |
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. |
topic |
multi-channel singular spectrum analysis geocenter motion prediction autoregressive moving average |
url |
https://www.mdpi.com/1424-8220/21/4/1403 |
work_keys_str_mv |
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