00000cam a22000004i 4500 UP-99796217612203150 Buklod 20160818155717.0 a grb 001 u| ta 130719s2013 xx a rb |001 0|eng d 9783642348358 (iLib)UPD-00257509913 E-38215 Fastbooks Php9,295.00 Dr. Ariel C. Blanco GE CaPaEBR DENG rda eng DMLUC TK 6561 L86 2013 Luo, Xiaoguang author. GPS stochastic modelling signal quality measures and ARMA processes Xiaoguang Luo. Heidelberg, Germany Springer-Verlag [2013] xxiii, 331 pages color illustrations 24 cm text rdacontent unmediated rdamedia volume rdacarrier "Doctoral Thesis accepted by the Karlsruhe Institute of Technology, Karlsruhe, Germany". Includes bibliographical references and index. 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. 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. Digital communications. Global Navigation satellite systems. Satellite positioning systems GE 154 College of Engineering, University of the Philippines Diliman. Satellite geodesy GE 168 College of Engineering, University of the Philippines Diliman. Satellite positioning systems GE 174 College of Engineering, University of the Philippines Diliman. Satellite geodesy GmE 211 College of Engineering, University of the Philippines Diliman. Satellite positioning, signal processing and numerical methods GmE 242 College of Engineering, University of the Philippines Diliman. FO UPD DENG TK 6561 L86 2013 Book