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Evaluation of the Possibility of Using the Predicted Tropospheric Delays in Real Time Gnss Positioning Cover

Evaluation of the Possibility of Using the Predicted Tropospheric Delays in Real Time Gnss Positioning

By: J. Z. Kalita,  Z. Rzepecka and  G. Krzan  
Open Access
|Dec 2014

Abstract

Among many sources of errors that influence Global Navigation Satellite System (GNSS) observations, tropospheric delay is one of the most significant. It causes nonrefractive systematic bias in the observations on the level of several meters, depending on the atmospheric conditions. Tropospheric delay modelling plays an important role in precise positioning. The current models use numerical weather data for precise estimation of the parameters that are provided as a part of the Global Geodetic Observation System (GGOS). The purpose of this paper is to analyze the tropospheric data provided by the GGOS Atmosphere Service conducted by the Vienna University of Technology. There are predicted and final delay data available at the Service. In real time tasks, only the predicted values can be used. Thus it is very useful to study accuracy of the forecast delays. Comparison of data sets based on predicted and real weather models allows for conclusions concerning possibility of using the former for real time positioning applications. The predicted values of the dry tropospheric delay component, both zenith and mapped, can be safely used in real time PPP applications, but on the other hand, while using the wet predicted values, one should be very careful.

DOI: https://doi.org/10.2478/arsa-2014-0014 | Journal eISSN: 2083-6104 | Journal ISSN: 1509-3859
Language: English
Page range: 179 - 189
Submitted on: Sep 9, 2014
Accepted on: Oct 13, 2014
Published on: Dec 30, 2014
Published by: Polish Academy of Sciences, Space Research Centre
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2014 J. Z. Kalita, Z. Rzepecka, G. Krzan, published by Polish Academy of Sciences, Space Research Centre
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.