Journal of Geodesy

, Volume 88, Issue 9, pp 887–900 | Cite as

Empirical modelling of site-specific errors in continuous GPS data

  • Michael Moore
  • Christopher Watson
  • Matt King
  • Simon McClusky
  • Paul Tregoning
Original Article


Continuous global positioning system (GPS) stations propagate biases and spurious signals into the derived parameter time series when the measurements are subject to site-specific effects, such as multipath. This is a particular problem in the investigation of geophysical and atmospheric phenomena where signals may be small in magnitude. A methodology to remove these erroneous signals from long-term time series will significantly increase the usefulness of the derived time series. This work provides the theoretical basis for use of an empirical site model (ESM) derived from post-fit phase residuals to mitigate unmodelled site-specific errors. Additionally, we also investigate the effectiveness of applying an ESM to a regional GPS network and a short baseline solution. Under most observing scenarios, we show that the ESM approach is predicted to improve the precision and accuracy of the site coordinates. However, it is important to note that we found some scenarios where the ESM can introduce a bias. For instance, when the antenna is mounted close to the ground. In this scenario, for a short baseline, we observed the introduction of a 4-mm bias in height. Use of an ESM for the same short baseline with an uncalibrated radome substantially improves the results by removing a large bias of over 10 mm in height. Similarly, application of an ESM derived from historic data yields similar improvements. This demonstrates that the ESM can be a powerful tool when applied to appropriate site-specific configurations and could potentially be implemented in routine GPS analysis for a broad range of applications.


Multipath Site-specific biases Carrier phase residuals 



The authors would like to thank Bob King and Thomas Herring for help with modifications to GAMIT and Track for this paper. We acknowledge Paul Cross’ comments from past work, which has formed the basis of the theoretical section of this paper and thank the reviewers of this paper, whose comments improved the manuscript. Michael Moore thanks Geoscience Australia for funding his PhD studies at ANU. Data and Products used were obtained from the ARGN and IGS network (Beutler et al. 2009). Processing and analysis of GPS data was carried out on the National Compute Infrastructure (Australia) through time allocation awarded to Geoscience Australia. M.A.K is a recipient of an Australian Research Council Future Fellowship (project number FT110100207).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Michael Moore
    • 1
    • 2
  • Christopher Watson
    • 3
  • Matt King
    • 3
  • Simon McClusky
    • 2
  • Paul Tregoning
    • 2
  1. 1.Geoscience AustraliaCanberraAustralia
  2. 2.Research School of Earth SciencesAustralian National UniversityCanberraAustralia
  3. 3.Surveying and Spatial Science Group, School of Geography and Environmental StudiesUniversity of TasmaniaHobartAustralia

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