Time-Correlated GPS Noise Dependency on Data Time Period

  • Alvaro Santamaría-GómezEmail author
  • Marie-Noëlle Bouin
  • Xavier Collilieux
  • Guy Wöppelmann
Conference paper
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 138)


GPS position time series contain time-correlated noise. The estimated parameters using correlated time series data, as station velocities, are then more uncertain than if the time series data were uncorrelated. If the level of the time-correlated noise is not taken into account, the estimated formal uncertainties will be smaller. By estimating the type and amplitude of the noise content in time series, more realistic formal uncertainties can be assessed.

However, time-correlated noise amplitude is not constant in long time series, but depends on the time period of the time series data. Older time series data contain larger time-correlated noise amplitudes than newer time series data. This way, shorter time series with older data time period exhibit time-correlated noise amplitudes similar to the whole time series. This paper focuses on the source of the time-correlated noise amplitude decrease from older to newer time series period data. The results of several tested sources are presented. Neither the increasing ambiguity fixation rate, nor the increasing number of tracking stations, nor the increasing number of observed satellites are likely the source of the noise reduction. The quality improvement of the equipment of both tracking network and constellation is likely the main source of the correlated noise evolution.


GPS Time series Time-correlated noise 



The authors acknowledge the invaluable technical support provided by Mikael Guichard, Marc-Henri Boisis-Delavaud and Frederic Bret from the IT Center of the University of La Rochelle. The University of La Rochelle computing infrastructure was partly funded by the European Union (Contract 31031–2008, European Regional Development Fund). This work was also feasible thanks to all institutions and individuals worldwide that contribute to make GPS data and products freely available (e.g., IGS, EPN, BIGF, GSI, RENAG, AMMA).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alvaro Santamaría-Gómez
    • 1
    • 2
    Email author
  • Marie-Noëlle Bouin
    • 3
  • Xavier Collilieux
    • 2
  • Guy Wöppelmann
    • 4
  1. 1.Instituto Geográfico NacionalYebesSpain
  2. 2.IGN/LAREG, Université Paris DiderotParisFrance
  3. 3.Centre National de Recherches MétéorologiquesBrestFrance
  4. 4.Fédération de Recherche en Environnement pour le Développement Durable (FR 3097 CNRS)Université de La Rochelle/CNRSLa RochelleFrance

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