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.
| ISBN: | 9783662511886 |
| Publication date: | 27th September 2016 |
| Author: | Xiaoguang Luo |
| Publisher: | Springer an imprint of Springer Berlin Heidelberg |
| Format: | Paperback |
| Pagination: | 331 pages |
| Series: | Springer Theses |
| Genres: |
Geographical information systems, geodata and remote sensing Electronics engineering Digital signal processing (DSP) Mathematical physics |
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.
GPS Stochastic Modelling features in the following genres: Geographical information systems, geodata and remote sensing, Electronics engineering, Digital signal processing (DSP), Mathematical physics
GPS Stochastic Modelling is available in Paperback, Hardback
GPS Stochastic Modelling was written by Xiaoguang Luo and published by Springer an imprint of Springer Berlin Heidelberg
GPS Stochastic Modelling has 331 pages
Yes it is part of Springer Theses series