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Analysis of the regional GNSS coordinate time series by ICA-weighted spatio-temporal filtering

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Abstract

Independent component analysis (ICA) is a blind source signal separation method which can effectively estimate high-order information and thus can effectively extract the common mode errors (CMEs) of a regional global navigation satellite system (GNSS) observation network. In this paper, ICA is used for the weighted filtering (WICA) and the extraction of CMEs of a regional GNSS observation network with the root mean square error (RMSE) of daily solution taken as the weighting factor. Through an analysis of the observed data from 19 valid stations of the Crustal Movement Observation Network of China (CMONOC) in North China, it is shown that the coordinate series precision of 13, 16 and 12 stations in the N, E and U directions, respectively, after filtering by WICA is higher than that by the traditional ICA method. The average correlation coefficient of the coordinate time series for each station after filtering is obviously decreased. Two simulation experiments are designed to extract known CMEs. It is shown that CMEs can be recovered better by WICA and that the standard deviations of most stations after filtering are smaller than those by ICA. The results from the real data and simulation experiments suggest that the RMSE of coordinate series be considered in spatio-temporal filtering.

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References

  • Amiri-Simkooei A R 2016 Non-negative least-squares variance component estimation with application to GPS time series; J. Geod. 90 451–466.

    Article  Google Scholar 

  • Blanz V and Vetter T 2002 Reconstructing the complete 3D shape of faces from partial information (Rekonstruktion der dreidimensionalen Form von Gesichternauspartieller information); Technische Informatik 44 295–302.

    Google Scholar 

  • Chen R, Tang B and Lv Z 2012 Ensemble empirical mode decomposition de-noising method based on correlation coefficients for vibration signal of rotor system; J. Vib. Meas. Diagn. 32(4) 542–546.

    Google Scholar 

  • Comon P 1994 Independent component analysis, a new concept? Signal. Process. 36 287–314.

    Article  Google Scholar 

  • Cui Y 2017 Tow ways of understanding the coefficient of correlation; Coll. Math. 33(3) 114–117.

    Google Scholar 

  • Dmitrieva K, Segall P and DeMets C 2015 Network-based estimation of time-dependent noise in GPS position time series; J. Geod. 89 591–606.

    Article  Google Scholar 

  • Dong D, Fang P, Bock Y, Webb F, Prawirodirdjo L, Kedar S and Jamason P 2006 Spatiotemporal filtering using principal component analysis and Karhunen-Loeve expansion approaches for regional GPS network analysis; J. Geophys. Res.-Solid Earth 111 3405–3421.

    Article  Google Scholar 

  • Gualandi A, Serpelloni E and Belardinelli M E 2016 Blind source separation problem in GPS time series; J. Geod. 90 323–341.

    Article  Google Scholar 

  • Li Q, You X, Yang S, Du R, Qiao X, Zou R and Wang Q 2012 A precise velocity field of tectonic deformation in China as inferred from intensive GPS observations; Sci. China Earth Sci. 55 695–698.

    Article  Google Scholar 

  • Li W, Shen Y and Li B 2015 Weighted spatiotemporal filtering using principal component analysis for analyzing regional GNSS position time series; Acta Geod. Geophys. 50 419–436.

    Google Scholar 

  • Liu B, Dai W, Peng W and Meng X 2015 Spatiotemporal analysis of GPS time series in vertical direction using independent component analysis; Earth Planets Space 67 189.

    Article  Google Scholar 

  • MárquezAzúa B and DeMets C 2003 Crustal velocity field of Mexico from continuous GPS measurements, 1993 to June 2001: Implications for the neotectonics of Mexico; J. Geophys. Res.-Solid Earth 108 149–169.

  • Ming F, Yang Y, Zeng A and Zhao B 2017 Spatiotemporal filtering for regional GPS network in China using independent component analysis; J. Geod. 91 419–440.

    Article  Google Scholar 

  • Nikolaidis R 2002 Observation of geodetic and seismic deformation with the global positioning system; Cancer Res. 71 714.

    Google Scholar 

  • Peng W, Dai W, Santerre R, Cai C and Kuang C 2017 GNSS vertical coordinate time series analysis using single-channel independent component analysis method; Pure Appl. Geophys. 174 265–278

    Google Scholar 

  • Shen Y, Li W, Xu G and Li B 2014 Spatiotemporal filtering of regional GNSS network’s position time series with missing data using principal component analysis; J. Geod. 88 1–12.

    Article  Google Scholar 

  • Shum H 1994 Principal component analysis with missing data and its application to object modeling; In: Conference on computer vision and pattern recognition, 1994. Proceedings CVPR’94, IEEE Computer Society, IEEE Trans. Pattern Anal. Mach. Intell. 17 854–867.

  • Tian Y and Shen Z 2009 Research progress on the removal of non-structural noise in GPS coordinate time series; Acta Seismol. Sin. 31 68–81.

    Google Scholar 

  • Tian Y and Shen Z 2011 Correlation weighted stacking filtering of common mode components in GPS observation network; Acta Seismol. Sin. 33 198–208.

    Google Scholar 

  • van Dam T, Wahr J, Milly P, Shmakin A B, Blewitt G, Lavallée D and Larson K M 2001 Crustal displacements due to continental water loading; Geophys. Res. Lett. 28 651–654.

    Article  Google Scholar 

  • Wang H, Liu M, Cao J, Shen X and Zhang G 2011a Slip rates and seismic moment deficits on major active faults in mainland China; J. Geophys. Res.-Solid Earth 116 1161–1172.

  • Wang M, Li Q, Wang F, Zhang R, Wang Y, Shi H, Zhang P and Shen Z 2011b Far-field coseismic displacements associated with the 2011 Tohoku-oki earthquake in Japan observed by global positioning system; Chin. Sci. Bull. 56 2419–2424.

    Article  Google Scholar 

  • Wdowinski S, Bock Y, Zhang J, Fang P and Genrich J 1997 Southern California permanent GPS geodetic array: Spatial filtering of daily positions for estimating coseismic and postseismic displacements induced by the 1992 Landers earthquake; J. Geophys. Res.-Solid Earth 102 18057–18070.

    Article  Google Scholar 

  • Williams S D P 2004 Error analysis of continuous GPS position time series; J. Geophys. Res.-Solid Earth 109 B03412.

  • Wu Y and Huang L 2004 A new interpolation method in time series analyzing; J. Geod. Geodyn. 24 43–47.

    Google Scholar 

  • Wu Y, Jiang Z, Wang M, Che S, Liao H, Li Q, Li P, Yang Y, Xiang H, Shao Z, Wang W, Wei W and Liu X 2013 Preliminary results pertaining to coseismic displacement and preseismic strain accumulation of the Lushan M S7.0 earthquake, as reflected by GPS surveying; Chin. Sci. Bull. 58 3460–3466.

    Article  Google Scholar 

  • Yang S, Li J and Wang Q 2008 The deformation pattern and fault rate in the Tianshan Mountains inferred from GPS observations; Sci. China Ser. D51 1064–1080.

    Article  Google Scholar 

  • Zhao B, Huang Y, Zhang C, Wang W, Tan K and Du R 2015 Crustal deformation on the Chinese mainland during 1998–2014 based on GPS data; Geod. Geodyn. 67 15.

    Google Scholar 

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Acknowledgements

This study was sponsored by the Natural Science Foundation of China (Grant No. 41774041). It was also supported by the key scientific and technological project of Henan province (Grant No. 172102210277) and the guiding programme for national coal association science and technology research (Grant No. MTKJ2016-212). We thank the China National Seismological Bureau Service Platform of Digital Products for providing GNSS continuous time series of the CMONOC. The reviewers and editors are acknowledged for their constructive comments. We are grateful to Keke Xu and Xiaoqi Wang from Henan Polytechnic University for the helpful discussions.

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Authors and Affiliations

  1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454003, People’s Republic of China

    Zheng Hou, Zengzhang Guo & Jiusheng Du

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  1. Zheng Hou
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  2. Zengzhang Guo
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  3. Jiusheng Du
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Correspondence to Zengzhang Guo.

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Communicated by Piyush Shanker Agram

Corresponding editor: Piyush Shanker Agram.

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Hou, Z., Guo, Z. & Du, J. Analysis of the regional GNSS coordinate time series by ICA-weighted spatio-temporal filtering. J Earth Syst Sci 128, 191 (2019). https://doi.org/10.1007/s12040-019-1214-6

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  • DOI: https://doi.org/10.1007/s12040-019-1214-6

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