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GPS Stochastic Modelling: Signal Quality Measures and ARMA Processes (Springer Theses) - Softcover

Luo, Xiaoguang

 
9783662511886: GPS Stochastic Modelling: Signal Quality Measures and ARMA Processes (Springer Theses)
Softcover
ISBN 10: 3662511886 ISBN 13: 9783662511886
Verlag: Springer, 2016

Inhaltsangabe

Global Navigation Satellite Systems (GNSS), such as GPS, have become an efficient, reliable and standard tool for a wide range of applications. However, when processing GNSS data, the stochastic model characterising the precision of observations and the correlations between them is usually simplified and incomplete, leading to overly optimistic accuracy estimates.

This work extends the stochastic model using signal-to-noise ratio (SNR) measurements and time series analysis of observation residuals. The proposed SNR-based observation weighting model significantly improves the results of GPS data analysis, while the temporal correlation of GPS observation noise can be efficiently described by means of autoregressive moving average (ARMA) processes. Furthermore, this work includes an up-to-date overview of the GNSS error effects and a comprehensive description of various mathematical methods.

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Über die Autorin bzw. den Autor

Xiaoguang Luo is currently a research associate at the Geodetic Institute of Karlsruhe Institute of Technology (KIT), Germany. He received his Ph.D. in Geodesy and Geoinformatics from KIT in 2012. He is interested in analysing the stochastic model, atmospheric and site-specific effects of GNSS observations, with a special focus on statistical testing and time series modelling.

Von der hinteren Coverseite

Global Navigation Satellite Systems (GNSS), such as GPS, have become an efficient, reliable and standard tool for a wide range of applications. However, when processing GNSS data, the stochastic model characterising the precision of observations and the correlations between them is usually simplified and incomplete, leading to overly optimistic accuracy estimates.

This work extends the stochastic model using signal-to-noise ratio (SNR) measurements and time series analysis of observation residuals. The proposed SNR-based observation weighting model significantly improves the results of GPS data analysis, while the temporal correlation of GPS observation noise can be efficiently described by means of autoregressive moving average (ARMA) processes. Furthermore, this work includes an up-to-date overview of the GNSS error effects and a comprehensive description of various mathematical methods.

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Verlag
Springer
Erscheinungsdatum
2016
Sprache
Englisch
ISBN 10 
3662511886
ISBN 13 
9783662511886
Einband
Taschenbuch
Anzahl der Seiten
356
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