Real-Time and Fast Retrieve the Coseismic Wave by GPS, Strong-Motion Combined Measurements and Broadcast Ephemeris

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 304)


In this study, we propose an approach of real-time and fast retrieving the coseismic waves by GPS, strong-motion combined measurements and broadcast ephemeris. Firstly, the velocity observation equations and state equations of the strong-motion measurements are introduced into Precise Point Positioning (PPP) solution model, the baseline shifts of the strong-motion are real-time estimated as unknown parameters like other positioning parameters by a Kalman filter. Then, the true velocity wave was retrieved by correcting the estimated baseline shifts, the true displacement wave was recovered by the velocity integrated displacement after de-trending a linear correction. The series of validation results have shown that, this method can fast and accurate retrieve the coseismic wave, the convergence time is smaller than one minute, and the precision are better than 2 mm/s and 2.5 cm for velocity and displacement respectively.


GPS and strong-motion combined measurements Broadcast ephemeris Coseismic wave retrieving Real-time 


  1. 1.
    McComb HE, Ruge AC, Neumann F (1943) The determination of true ground motion by integration of strong-motion records: a symposium. Bull Seismol Soc Am 33:1–63Google Scholar
  2. 2.
    Graizer VM (1979) Determination of the true ground displacement by using strong motion records. Izv Earth Phys 25:26–29Google Scholar
  3. 3.
    Chiu H (1997) Stable baseline correction of digital strong-motion data. Bull Seism Soc Am 87:932–944Google Scholar
  4. 4.
    Zhu L (2003) Recovering permanent displacements from seismic records of the June 9, 1994 Bolivia deep earthquake. Geophys Res Lett 30:1740. doi: 10.1029/2003GL017302 CrossRefGoogle Scholar
  5. 5.
    Elósegui P, Davis JL, Oberlander D, Baena R, Ekströ G (2006) Accuracy of high-rate GPS for seismology. Geophys Res Lett 33:L11308. doi: 10.1029/2006GL026065 CrossRefGoogle Scholar
  6. 6.
    Genrich JF, Bock Y (2006) Instantaneous geodetic positioning with 10–50 Hz GPS measurements: noise characteristics and implicationsfor monitoring networks. J Geophys Res 111:B03403. doi: 10.1029/2005JB003617 Google Scholar
  7. 7.
    Larson KM, Bilich A, Axelrad P (2007) Improving the precision of high-rate GPS. J Geophys Res 112:B05422. doi: 10.1029/2006JB004367 Google Scholar
  8. 8.
    Iwan W, Moser M, Peng C (1985) Some observations on strong-motion earthquake measurement using a digital accelerograph. Bull Seism Soc Am 75:1225–1246Google Scholar
  9. 9.
    Boore DM (2001) Effect of baseline corrections on displacement and response spectra for several recordings of the 1999 Chi-Chi, Taiwan, earthquake. Bull Seism Soc Am 91:1199–1211CrossRefGoogle Scholar
  10. 10.
    Graizer V (2006) Tilts in strong ground motion. Bull Seism Soc Am 96:2090–2106CrossRefGoogle Scholar
  11. 11.
    Wu Y, Wu C (2007) Approximate recovery of coseismic deformation from Taiwan strong-motion records. J Seismol 11:159–170CrossRefGoogle Scholar
  12. 12.
    Wang R, Schurr B, Milkereit C, Shao Zh, Jin M (2011) An improved automatic scheme for empirical baseline correction of digital strong-motion records. Bull Seism Soc Am 101:2029–2044CrossRefGoogle Scholar
  13. 13.
    Bock Y, Melgar D, Crowell BW (2011) Real-time strong-motion broadband displacements from collocated GPS and accelerometers. Bull Seism Soc Am 101:2904–2925CrossRefGoogle Scholar
  14. 14.
    Wang R, Parolai S, Ge M, Jin MP, Walter TR, Zschau J (2013) The 2011 Mw 9.0 Tohoku earthquake: comparison of GPS and strong-motion data. Bull Seism Soc Am. doi: 10.1785/0120110264
  15. 15.
    Tu R, Wang R, Ge M, Walter TR, Ramatschi M, Milkereit C, Bindi D, Dahm T (2013a) Cost effective monitoring of broadband strong ground motion related to earthquakes, landslides or volcanic activities by joint use of a single-frequency GPS and a MEMS-type accelerometer. Geophys Res Lett. doi: 10.1002/grl.50653
  16. 16.
    Geng J, Bock Y, Melgar D, Crowell BW, Haase JS (2013) A new seismogeodetic approach applied to GPS and accelerometer observations of the 2011 Brawly seismic swarm: implications for earthquake early warning. Geophys Geosyst, Geochem. doi: 10.1002/ggge.20144 Google Scholar
  17. 17.
    Li X, Ge M, Zhang Y, Wang R, Klotz J, Wicket J (2013) Tightly integrated processing of high-rate GPS and strong-motion data: Application to earthquake early warning. Geophys J Int. doi: 10.1093/gji/ggt249
  18. 18.
    Zumberge JF, Heflin MB, Jefferson DC, Watkins M (1997) Precise point positioning for the efficient and robust analysis of GPS data from large networks. J Geophys Res 102:5005–5017CrossRefGoogle Scholar
  19. 19.
    Bisnath S., Gao Y (2007) Current state of precise point positioning and future prospects and limitations. Observing our changing earth, international association of Geodesy Symposia 133, Springer-Verlag. Berlin HeidelbergGoogle Scholar
  20. 20.
    Dach R, Hugentobler U, Fridez P, Michael M (eds) (2007) Bernese GPS software version 5.0. Astronomical Institute, University of BernGoogle Scholar
  21. 21.
    Kouba J, Héroux P (2001) Precise point positioning using IGS orbit and clock products. GPS Solut 5(2):12–28. doi: 10.1007/PL00012883 CrossRefGoogle Scholar
  22. 22.
    Tu R, Ge M, Wang R, Walter TR (2013) Real-time seismic data processing: a new algorithm for tight integration of high-rate GPS and strong-motion records, demonstrated for experimental data and the 2010 Baja California earthquake (Mw 7.2). J Seismol. doi: 10.1007/s10950-013-9408-x Google Scholar
  23. 23.
    Smyth A, Wu M (2006) Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring. Mech Syst Signal Process 21:706–723CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.The Germany Research Center for GeosciencesPotsdamGermany

Personalised recommendations