LEADER 00000nam a22004695i 4500 
001    978-3-642-34836-5 
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005    20151204141812.0 
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008    130706s2013    gw |    s    |||| 0|eng d 
020    9783642348365|9978-3-642-34836-5 
024 7  10.1007/978-3-642-34836-5|2doi 
040    ES-ZaU 
072  7 RGW|2bicssc 
072  7 TEC036000|2bisacsh 
082 04 910.285|223 
100 1  Luo, Xiaoguang.|eauthor. 
245 10 GPS Stochastic Modelling|h[electronic resource] :|bSignal 
       Quality Measures and ARMA Processes /|cby Xiaoguang Luo. 
260  1 Berlin, Heidelberg :|bSpringer Berlin Heidelberg :
       |bImprint: Springer,|c2013. 
300    XXIII, 331 p. 129 illus., 127 illus. in color.|bonline 
       resource. 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file|bPDF|2rda 
490 1  Springer Theses, Recognizing Outstanding Ph.D. Research,
       |x2190-5053 
490 0  Springer eBooks.|aEarth and Environmental Science 
505 0  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. 
520    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. 
650  0 Geography. 
650  0 Remote sensing. 
650  0 Mathematical physics. 
650 14 Geography. 
650 24 Remote Sensing/Photogrammetry. 
650 24 Mathematical Applications in the Physical Sciences. 
650 24 Signal, Image and Speech Processing. 
710 2  SpringerLink (Online service) 
773 0  |tSpringer eBooks 
776 08 |iPrinted edition:|z9783642348358 
830  0 Springer Theses, Recognizing Outstanding Ph.D. Research,
       |x2190-5053 
856 40 |uhttps://cuarzo.unizar.es:9443/login?url=https://
       dx.doi.org/10.1007/978-3-642-34836-5|zAcceso al texto 
       completo