Python Software Tool for Diagnostics of the Global Navigation Satellite System Station (PS-NETM)–Reviewing the New Global Navigation Satellite System Time Series Analysis Tool

The time series of GNSS coordinates contain signals caused by the age-related movement of tectonic plates, the deformation of the Earth’s surface, as well as errors at different time scales from sub-daily tidal deformation to the long-term deformation of the surface load. Depending on the nature of...

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Vydáno v:	Remote sensing (Basel, Switzerland) Ročník 16; číslo 5; s. 757
Hlavní autoři:	Savchuk, Stepan, Dvulit, Petro, Kerker, Vladyslav, Michalski, Daniel, Michalska, Anna
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.03.2024
Témata:	Age Artificial satellites in navigation Calibration Computer programs computer software deformation diagnostic techniques Earth surface Error analysis Europe Global navigation satellite system global positioning systems GNSS time series Information processing Methods non-classical error theory Normal distribution Normality Orbits Pearson–Jeffreys distribution Plates (tectonics) Python (programming language) Satellites Science Software Software packages spatio-temporal filtering Statistical analysis Systematic errors Technology application tectonics Time series time series analysis Poland Europe
ISSN:	2072-4292, 2072-4292
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Abstract	The time series of GNSS coordinates contain signals caused by the age-related movement of tectonic plates, the deformation of the Earth’s surface, as well as errors at different time scales from sub-daily tidal deformation to the long-term deformation of the surface load. Depending on the nature of the signal, specific approaches are used for both the visual interpretation and pre-processing of time series and their statistical analysis. However, none of the present software analyzes the nature of the residual errors but assumes their random nature and obedience to the classical normal distribution. One of the methods for analyzing the time series of coordinates with residual, unaccounted-for systematic errors is the non-classical error theory of measurements. The result of this work is a developed software solution for analyzing the time series of GNSS coordinates to test their normality, or in other words, to test whether a particular GNSS station is subject to the influence of small, unaccounted-for errors. Conclusions: After testing our software on four reference stations in Europe, we concluded that none of the chosen stations followed the normal law of distribution; thus, it is vital to perform such tests before conducting any experiments on the time series from reference stations.
AbstractList	The time series of GNSS coordinates contain signals caused by the age-related movement of tectonic plates, the deformation of the Earth’s surface, as well as errors at different time scales from sub-daily tidal deformation to the long-term deformation of the surface load. Depending on the nature of the signal, specific approaches are used for both the visual interpretation and pre-processing of time series and their statistical analysis. However, none of the present software analyzes the nature of the residual errors but assumes their random nature and obedience to the classical normal distribution. One of the methods for analyzing the time series of coordinates with residual, unaccounted-for systematic errors is the non-classical error theory of measurements. The result of this work is a developed software solution for analyzing the time series of GNSS coordinates to test their normality, or in other words, to test whether a particular GNSS station is subject to the influence of small, unaccounted-for errors. Conclusions: After testing our software on four reference stations in Europe, we concluded that none of the chosen stations followed the normal law of distribution; thus, it is vital to perform such tests before conducting any experiments on the time series from reference stations.
Audience	Academic
Author	Savchuk, Stepan Michalska, Anna Dvulit, Petro Kerker, Vladyslav Michalski, Daniel
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Cites_doi	10.1002/2015JB012253 10.1088/1742-6596/1614/1/012082 10.1029/2009JB006543 10.21105/joss.01237 10.1007/s00190-016-0973-y 10.1007/s10291-014-0386-4 10.1007/978-3-030-21718-1 10.1029/2005JB003806 10.1007/s10291-017-0637-2 10.1007/s10291-019-0846-y 10.3390/rs12213532 10.3390/engproc2021005021 10.1016/j.jog.2017.01.004 10.2478/arsa-2021-0008 10.1098/rspa.1998.0193 10.1029/2018JB016783 10.1007/s10291-019-0888-1
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SubjectTerms	Age Artificial satellites in navigation Calibration Computer programs computer software deformation diagnostic techniques Earth surface Error analysis Europe Global navigation satellite system global positioning systems GNSS time series Information processing Methods non-classical error theory Normal distribution Normality Orbits Pearson–Jeffreys distribution Plates (tectonics) Python (programming language) Satellites Science Software Software packages spatio-temporal filtering Statistical analysis Systematic errors Technology application tectonics Time series time series analysis
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Title	Python Software Tool for Diagnostics of the Global Navigation Satellite System Station (PS-NETM)–Reviewing the New Global Navigation Satellite System Time Series Analysis Tool
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