Articles | Volume 10, issue 1
https://doi.org/10.5194/se-10-329-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-10-329-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Feb 2019
Research article |
| 15 Feb 2019
| 15 Feb 2019
Precision of continuous GPS velocities from statistical analysis of synthetic time series
Christine Masson
CORRESPONDING AUTHOR
Géosciences Montpellier, CNRS, University of Montpellier,
Université des Antilles, Montpellier, 34000, France
Stephane Mazzotti
Géosciences Montpellier, CNRS, University of Montpellier,
Université des Antilles, Montpellier, 34000, France
Philippe Vernant
Géosciences Montpellier, CNRS, University of Montpellier,
Université des Antilles, Montpellier, 34000, France
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Short summary
We use statistical analyses of synthetic position time series to estimate the potential precision of GPS velocities. Regression tree analyses show that the main factors controlling the velocity precision are the duration of the series, the presence of offsets, and the noise. Our analysis allows us to propose guidelines which can be applied to actual GPS data that constrain the velocity accuracies.
We use statistical analyses of synthetic position time series to estimate the potential...
