GNSS vertical coordinate time series analysis using single-channel independent component analysis method

Authors: Peng, Wei; Dai, Wujiao; Santerre, Rock; Changsheng, Cai; Kuang, Cuilin
Abstract: Daily vertical coordinate time series of Global Navigation Satellite System (GNSS) stations usually contains tectonic and non-tectonic deformation signals, residual atmospheric delay signals, measurement noise, etc. In geophysical studies, it is very important to separate various geophysical signals from the GNSS time series to truthfully reflect the effect of mass loadings on crustal deformation. Based on the independence of mass loadings, we combine the Ensemble Empirical Mode Decomposition (EEMD) with the Phase Space Reconstruction-based Independent Component Analysis (PSR-ICA) method to analyze the vertical time series of GNSS reference stations. In the simulation experiment, the seasonal non-tectonic signal is simulated by the sum of the correction of atmospheric mass loading and soil moisture mass loading. The simulated seasonal non-tectonic signal can be separated into two independent signals using the PSR-ICA method, which strongly correlated with atmospheric mass loading and soil moisture mass loading, respectively. Likewise, in the analysis of the vertical time series of GNSS reference stations of Crustal Movement Observation Network of China (CMONOC), similar results have been obtained using the combined EEMD and PSR-ICA method. All these results indicate that the EEMD and PSR-ICA method can effectively separate the independent atmospheric and soil moisture mass loading signals and illustrate the significant cause of the seasonal variation of GNSS vertical time series in the mainland of China.
Document Type: Article de recherche
Issue Date: 14 May 2016
Open Access Date: Restricted access
Document version: VoR
This document was published in: Pure and Applied Geophysics, Vol. 174 (2), 723–736 (2017)
Alternative version: 10.1007/s00024-016-1309-9
Collection:Articles publiés dans des revues avec comité de lecture

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