Advertisement

Earth, Planets and Space

, Volume 52, Issue 10, pp 837–840 | Cite as

Real-time deformation monitoring with GPS and Kalman Filter

  • Cankut D. Ince
  • Muhammed Sahin
Open Access
Letter

Abstract

The main purpose of this research is to develop a real-time GPS monitoring system with the aid of a Kalman Filter for use in an active tectonic region near Istanbul, and its surrounding region. Currently, an ongoing project exists, funded by the World Bank, that monitors deformation in Istanbul and the Marmara Region. Istanbul is one of the largest cities in the world, and is under possible earthquake threat. In order to set up a powerful control system, a surveying and estimation method was designed and the necessary software, called RT-MODS2 (Real-Time Monitoring Of Dynamic Systems 2), was developed. The software reads real-time input data from GPS receivers and performs deformation analyses with the help of the Kalman Filter. Some studies of filtering and deformation analysis were performed in order to detect failures and outliers, and to increase the reliability of the deformation analysis.

Keywords

Kalman Filter Deformation Analysis Marmara Region NMEA Powerful Control System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Barka, A., The August 17 and November 12 1999 Earthquakes in the Eastern Marmara Sea Region, International Symposiumon the Kocaeli Earthquake, Istanbul, December 2–5, 1999.Google Scholar
  2. Bennet, R. A., B. P. Wernicke, and J. L. Davis, Continuous GPS measurements of contemporary deformation across the northern basin and range province, Geophys. Res. Lett., 25(4), 1998.Google Scholar
  3. Bock, Y. and M. Bevis, Regional Permanent GPS Arrays. Trends and Prospects, International Symposium on GPS, Tsukuba, Japan, October 18–22, 1999.Google Scholar
  4. Cross, P. A., Advanced Least Squares Applied to Position-Fixing, North East London Working paper No. 6 Polytechnic, Department of Land Surveying, 1990.Google Scholar
  5. Grewal, M. S. and A. P. Andrews, Kalman Filtering Theory and Practice, 380 pp., Prentice Hall, Englewood Cliffs, New Jersey, 1993.Google Scholar
  6. Hofmann-Wellenhof, B., H. Lichtenegger, and J. Collins, GPS Theory and Practice, 370 pp., 4th edition, Springer Verlag, Wien New York, 1997.Google Scholar
  7. Ince, C. D., Real-time monitoring of Dynamic Systems with GPS and Kalman Filter, Ph.D. thesis, Istanbul Technical University, 154 pp., 1999 (in Turkish).Google Scholar
  8. Jin, X. X., Theory of Carrier Adjusted DGPS Positioning Approach and Some Experimental Results, Delft University Press, Netherlands, 164 pp., 1996.Google Scholar
  9. Kalman, R. E., A new approach to linear filtering and prediction problems, Journal of Basic Engineering, 82D, 35–45, 1960.CrossRefGoogle Scholar
  10. Kalman, R. E. and R. S. Bucy, New results in linear filtering and prediction theory, Journal of Basic Engineering, 83D, 95–108, 1961.CrossRefGoogle Scholar
  11. Langley, R. B., NMEA 0183: AGPS Receiver Interface Standard, GPS World, 54–57, July 1995.Google Scholar
  12. Leick, A., GPS Satellite Surveying, John Wiley and Sons, Inc., 584 pp., 1995.Google Scholar
  13. Maybeck, P. S., Stochastic Models, Estimation and Control Volume I, 423 pp., Academic Press, Inc., New York, 1979.Google Scholar
  14. Salzmann, M., MDB: A Design Tool for Integrated Navigation Systems, Kinematic Systems in Geodesy, Surveying and Remote Sensing Symposium No. 107, Banff, Alberta, Canada, September 10–13, pp. 218–227, 1990.Google Scholar
  15. Teunissen, P. J. G., Some Aspects of Real-Time Validation Techniques for Use in Integrated Systems, Kinematic Systems in Geodesy, Surveying and Remote Sensing Symposium No. 107, Banff, Alberta, Canada, September 10–13, pp. 191–200, 1990.Google Scholar
  16. Teunissen, P. J. G. and M. A. Salzmann, Performance Analysis of Kalman Filters, Reports 88.2, Delft University of Technology, The Faculty of Geodesy, Mathematical and Physical Geodesy, Netherlands, 1988.Google Scholar
  17. Tsai, C. and L. Kurz, An adaptive robustizing approach to Kalman Filtering, Automatica, 19, 279–288, 1983.CrossRefGoogle Scholar

Copyright information

© The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences. 2000

Authors and Affiliations

  • Cankut D. Ince
    • 1
  • Muhammed Sahin
    • 1
  1. 1.Department of Geodesy and PhotogrammetryIstanbul Technical University, Faculty of Civil EngineeringIstanbulTurkey

Personalised recommendations