Skip to main content
SpringerLink
Log in

Analysis of GNSS Coordinate Time Series in North China by Independent Component Analysis

  • Conference paper
  • First Online:
China Satellite Navigation Conference (CSNC 2024) Proceedings (CSNC 2024)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1092))

Included in the following conference series:

  • 260 Accesses

Abstract

Common mode error (CME), as a kind of non-tectonic motion, is one of the most important error sources in Global Navigation Satellite System (GNSS) coordinate time series. In order to obtain a precise and reliable velocity at a station, the influence of CME should be removed or decreased. In this paper, independent component analysis (ICA) method is applied to extract CMEs and analyze their influences on the coordinate time series based on 24 GNSS reference stations in North China during 2011–2020 period. The results indicate that, (1) After CMEs filtered out by the ICA, the average correlation coefficients between the residual time series decrease from previously 0.5–0.7 to −0.04 in east, north and up directions at stations, implying that the strong correlation between the residual time series at stations is significantly reduced by the ICA filtering. (2) The RMS of residual time series is effectively suppressed after the ICA filtering, with the RMS decreasing about 43.95%, 52.25% and 38.13% in east, north and up direction, respectively. (3) The averages of uncertainties of velocity estimations are decreasing from 0.30, 0.27 and 0.42 mm/yr to 0.12, 0.09 and 0.22 mm/yr in east, north and up direction before and after the ICA filtering, respectively, showing that the precision of the velocity estimation is improved about 60%, 69% and 49% in the three directions. Therefore, it is necessary to do the filtering among the GNSS coordinate time series to remove the effect of CME and the ICA is demonstrated to be an effective method to apply the filtering, so as to extract the precise tectonic motion in North China.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Jiang, W., Wang, K., Li, Z., Zhou, X., Ma, Y., Ma, J.: Prospect and theory of GNSS coordinate time series analysis. Geomat. Inf. Sci. Wuhan Univ. 43(12), 2112–2123 (2018)

    Google Scholar 

  2. Gan, W., Zhang, R., Zhang, Y., Tang, F.: Development of the crustal movement observation network in China and its applications. Recent Dev. World Seism. 343(7), 43–52 (2007)

    Google Scholar 

  3. Sheng, C., Gan, W., Liang, S., Chen, W., Xiao, G.: Identification and elimination of non-tectonic crustal deformation caused by land water from GPS time series in the western Yunnan province based on GRACE observations. Chin. J. Geophys. 57(1), 42–52 (2014)

    Google Scholar 

  4. Wang, M., Shen, Z., Dong, D.: Effects of non-tectonic crustal deformation on continuous GPS position time series and correction to them. Chin. J. Geophys. 48(5), 1045–1052 (2005)

    Article  Google Scholar 

  5. Yuan, L., et al.: Characteristics of daily position time series from the Hong Kong GPS fiducial network. Chin. J. Geophys. 51(5), 1372–1384 (2008)

    Article  Google Scholar 

  6. Wdowinski, S., Bock, Y., Zhang, J., Fang, P., Genrich, J.: 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(B8), 18057–18070 (1997)

    Article  Google Scholar 

  7. Li, F., Li, W., Zhang, S., Lei, J., Zhang, Q., Yuan, L.: Spatiotemporal filtering for regional GNSS network in Antarctic Peninsula using independent component analysis. Chin. J. Geophys. 62(9), 3279–3295 (2019)

    Google Scholar 

  8. Ming, F., Yang, Y., Zeng, A., Zhao, B.: Spatiotemporal filtering for regional GPS network in China using independent component analysis. J. Geodesy 91(4), 419–440 (2017)

    Article  Google Scholar 

  9. Dong, D., et al.: Spatiotemporal filtering using principal component analysis and Karhunen-Loeve expansion approaches for regional GPS network analysis. J. Geophys. Res.: Solid Earth 111(B3), 3405–3421 (2006)

    Google Scholar 

  10. Yao, Y., Ran, Q., Zhang, B.: Influence of common mode error on the estimation velocity field of CMONOC’s stations. J. Geomat. 44(3), 1–6 (2019)

    Google Scholar 

  11. Langbein, J., Johnson, H.: Correlated errors in geodetic time series: implications for time-dependent deformation. J. Geophys. Res.: Solid Earth 102(B1), 591–603 (1997)

    Article  Google Scholar 

  12. Hu, S., Wu, J., Sun, Y.: Comparison among three spatiotemporal filtering methods for regional GPS networks analysis. J. Geod. Geodyn. 29(3), 95–99 (2009)

    Google Scholar 

  13. Xie, S., Pan, P., Zhou, X.: Research on common mode error extraction method for large-scale GPS network. Geomat. Inf. Sci. Wuhan Univ. 39(10), 1168–1173 (2014)

    Google Scholar 

  14. Tian, Y., Shen, Z.: Correlation weighted stacking filtering of common mode component in GPS observation network. Acta Seismol. Sin. 33(2), 198–208 (2011)

    Google Scholar 

  15. Ming, F.: Research on the GPS coordinate time series analysis. Strategic Support Force Information Engineering University (2018)

    Google Scholar 

  16. Ming, F., Yang, Y., Zeng, A.: Analysis and comparison of common mode error extraction using principal component analysis and independent component analysis. J. Geod. Geodyn. 37(4), 385–389 (2017)

    Google Scholar 

  17. Zhou, W., Ding, K., Liu, P., Lan, G., Ming, Z.: Spatiotemporal filtering for continuous GPS coordinate time series in mainland China by using independent component analysis. Remote Sens. 14(12), 2904 (2022)

    Article  Google Scholar 

  18. Ding, K., Freymueller, J.T., Wang, Q., Zou, R.: Coseismic and early postseismic deformation of the 5 January 2013 Craig Mw 7.5 earthquake from GPS static and kinematic solutions. Bull. Seismol. Soc. Am. 105 (2015)

    Google Scholar 

  19. Nikolaidis, R.: Observation of geodetic and seismic deformation with the Global Positioning System. University of California, San Diego (2002)

    Google Scholar 

  20. Tian, Y., Shen, Z., Li, P.: Analysis on correlated noise in continuous GPS observations. Acta Seismol. Sin. 6, 696–704 (2010)

    Google Scholar 

  21. Wu, W., Meng, G., Wu, J.: Noise in GPS coordinate time series for North China fiducial stations. J. Geod. Geodyn. 36(8), 708–713 (2016)

    Google Scholar 

  22. Jiang, Z., Zhang, P., Bi, J., Liu, L.: Velocity estimation on the colored noise properties of CORS network in China based on the CGCS2000 frame. Acta Geod. Cartogr. Sin. 39(4), 355–363 (2010)

    Google Scholar 

  23. Williams, S.D.P.: The effect of coloured noise on the uncertainties of rates estimated from geodetic time series. J. Geodesy 76(9), 483–494 (2003)

    Google Scholar 

  24. Ding, K., Ding, J., Li, Z., Wang, L.: Analysis on noise model of GNSS base station from CMONOC in Sichuan-Yunnan region. Sci. Surv. Mapp. 39(12), 56–60 (2014)

    Google Scholar 

  25. Huang, L., Fu, Y.: Analysis on the noises from continuously monitoring GPS sites. Acta Seismol. Sin. 29(2), 197–202 (2007)

    Google Scholar 

  26. Bos, M.S., Fernandes, R.M.S., Williams, S.D.P., Bastos, L.: Fast error analysis of continuous GNSS observations with missing data. J. Geodesy 87(4), 351–360 (2013)

    Article  Google Scholar 

  27. Peres-Neto, P.R., Jackson, D.A., Somers, K.M.: How many principal components? Stopping rules for determining the number of non-trivial axes revisited. Comput. Stat. Data Anal. 49(4), 974–997 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  28. Hyvarinen, A.: Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Networks 10(3), 626–634 (1999)

    Article  Google Scholar 

  29. Hyvärinen, A., Oja, E.: Independent component analysis: algorithms and applications. Neural Netw. 13(4–5), 411–430 (2000)

    Article  Google Scholar 

  30. Tichavsky, P., Koldovsky, Z., Oja, E.: Corrections to “performance analysis of the FastICA algorithm and Cramér-Rao bounds for linear independent component analysis.” IEEE Trans. Signal Process. 56(4), 1715–1716 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  31. Wang, F., Lü, Z., Lü, H., Kuang, Y.: Application analysis of GPS coordinate time series interpolation based on RegEM algorithm. J. Geod. Geodyn. 40(1), 45–50 (2020)

    Google Scholar 

  32. Ming, F., Zeng, A., Gou, W., Xu, K.: Analysis of the sensitivity of data-driven interpolation algorithm to GNSS coordinate time series. Geomat. Sci. Eng. 36(5), 4–9 (2016)

    Google Scholar 

  33. Schneider, T.: Analysis of incomplete climate data: estimation of mean values and covariance matrices and imputation of missing values. J. Clim. 14(5), 853–871 (2001)

    Article  Google Scholar 

  34. Yuan, P., Jiang, W., Wang, K., Sneeuw, N.: Effects of spatiotemporal filtering on the periodic signals and noise in the GPS position time series of the Crustal Movement Observation Network of China. Remote Sens. 10(9), 1472 (2018)

    Article  Google Scholar 

  35. Zhang, T., Shen, W.B., Wu, W., Zhang, B., Pan, Y.: Recent surface deformation in the Tianjin area revealed by Sentinel-1A data. Remote Sens. 11(2), 130 (2019)

    Article  Google Scholar 

  36. Li, S., Shen, W., Pan, Y., Zhang, T.: Surface seasonal mass changes and vertical crustal deformation in North China from GPS and GRACE measurements. Geod. Geodyn. 11(1), 46–55 (2020)

    Article  Google Scholar 

  37. Feng, T., Shen, Y., Wang, F.: Independent component extraction from the incomplete coordinate time series of regional GNSS networks. Sensors 21(5), 1569 (2021)

    Article  Google Scholar 

  38. Serpelloni, E., Faccenna, C., Spada, G., Dong, D., Williams, S.D.: Vertical GPS ground motion rates in the Euro-Mediterranean region: new evidence of velocity gradients at different spatial scales along the Nubia-Eurasia plate boundary. J. Geophys. Res.: Solid Earth 118(11), 6003–6024 (2013)

    Article  Google Scholar 

  39. Tian, Y., Shen, Z.: Progress on reduction of non-tectonic noise in GPS position time series. Acta Seismol. Sin. 31(1), 68–81 (2009)

    Google Scholar 

  40. Lyu, J., Yang, C.: Vertical motion analysis of North China using large area precision leveling and GPS data. North China Earthq. Sci. 33(3), 22–25 (2015)

    Google Scholar 

  41. Zhang, Y., Wu, H., Kang, H.: Ground subsidence over Beijing-Tianjin-Hebei region during three periods of 1992 to 2014 monitored by interferometric SAR. Acta Geod. Cartogr. Sin. 45(9), 1050–1058 (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430074, China

    Guanghong Lan & Kaihua Ding

Authors
  1. Guanghong Lan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kaihua Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kaihua Ding .

Editor information

Editors and Affiliations

  1. China Satellite Navigation Engineering Centre, Beijing, China

    Changfeng Yang

  2. China Academy of Space Technology, Beijing, China

    Jun Xie

Rights and permissions

Reprints and permissions

Copyright information

© 2024 Aerospace Information Research Institute

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lan, G., Ding, K. (2024). Analysis of GNSS Coordinate Time Series in North China by Independent Component Analysis. In: Yang, C., Xie, J. (eds) China Satellite Navigation Conference (CSNC 2024) Proceedings. CSNC 2024. Lecture Notes in Electrical Engineering, vol 1092. Springer, Singapore. https://doi.org/10.1007/978-981-99-6928-9_19

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-6928-9_19

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6927-2

  • Online ISBN: 978-981-99-6928-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation