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The continuous GNSS stations are used to determine the displacement velocities, seasonal variation, amplitude of tectonic activities,… To accurately determine these factors, the first is to remove outliers in GNSS position time series. In general, filtering approaches are subjectively selected based on the experience and visual interpretation of experts. Therefore, the process may lead to a waste of time or confusion, especially for stations with long-term continuously recorded data. The purpose of paper is to introduce the applicability of several algorithms and methods of filtering outliers in GNSS position time series.

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Article Details

Issue: Vol 19 No 2 (2016)
Page No.: 43-50
Published: Jun 30, 2016
Section: Engineering and Technology - Research article

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Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Tran, T., Dao, T., Vu, T., Luong, D., Vu, C., Bui, S., & Ha, H. (2016). Outlier detection in GNSS position time series. Science and Technology Development Journal, 19(2), 43-50.

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