TY  - BOOK
AU  - Luo,Xiaoguang
ED  - SpringerLink (Online service)
TI  - GPS Stochastic Modelling: Signal Quality Measures and ARMA Processes 
T2  - Springer Theses, Recognizing Outstanding Ph.D. Research,
SN  - 9783642348365
AV  - GA102.4.R44 
U1  - 910.285 23
PY  - 2013///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Geography
KW  - Remote sensing
KW  - Mathematical physics
KW  - Remote Sensing/Photogrammetry
KW  - Mathematical Applications in the Physical Sciences
KW  - Signal, Image and Speech Processing
N1  - Introduction -- Mathematical Background -- Mathematical Models for GPS Positioning -- Data and GPS Processing Strategies -- Observation Weighting Using Signal Quality Measures -- Results of SNR-based Observation Weighting -- Residual-based Temporal Correlation Modelling -- Results of Residual-based Temporal Correlation Modelling -- Conclusions and Recommendations -- Quantiles of Test Statistics -- Derivations of Equations -- Additional Graphs -- Additional Tables
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-642-34836-5
ER  -