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Error Detection in GPS Observations by Means of Multi-Process Models

  • Enrik F. Thomsen
Conference paper
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 122)

Abstract

The main purpose of this article is to present the idea of using Multi-process models as a method of detecting errors in GPS observations.

The theory behind Multi-process models, and. double differenced phase observations in GPS is presented shortly.

It is shown how to model cycle slips in the Multi-process context by means of a simple simulation. The simulation is used to illustrate how the method works, and it is concluded that the method deserves further investigation.

Keywords

Dynamic Linear Modeling Kaiman filter detection of cycle slips GPS 

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References

  1. Gammelgaard, S., Milsgaard, M., and Mortensen, R. (1995). Monitoring by using Dynamical Linear Models-illustrated by tumor markers for cancer. Master’s thesis, Aalborg University. 180Google Scholar
  2. Parkinson, B. and Spilker Jr., J. (1996). Global positioning system: Theory and Applications, Volume 2. In Parkinson, B. and Spilker Jr., J., editors, Progress in Astronautics and Aeronautics, volume 163.Google Scholar
  3. Sansò, F. and Venuti, G. (1997). Integer variables estimation problems: the Bayesan approach. ANNALI DI GEOFISICA, XL(5):1415–1431.Google Scholar
  4. Strang, G. and Borre, K. (1997). Linear Algebra, Geodesy, and GPS. Wellesley-Cambridge Press.Google Scholar
  5. Teunisen, P., de Jonge, P., and Tiberius, C. (1997). Performance of the LAMBDA Method for Fast GPS Ambiguity Resolution. Navigation: Journal of The Institute of Navigation, 44(3).Google Scholar
  6. West, M. and Harrison, J. (1997). Bayesan Forecasting and Dynamic Models. Springier-Verlag. second edition.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Enrik F. Thomsen
    • 1
  1. 1.Aalborg UniversityAalborg ØDenmark

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