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Añadir al carritoTaschenbuch. Condición: Neu. GPS Stochastic Modelling | Signal Quality Measures and ARMA Processes | Xiaoguang Luo | Taschenbuch | Springer Theses | xxiii | Englisch | 2016 | Springer | EAN 9783662511886 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Seiten: 356 | Sprache: Englisch | Produktart: Bücher | 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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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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Añadir al carritoHardcover. Condición: Brand New. 2014 edition. 280 pages. 9.20x6.10x1.00 inches. In Stock.
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Publicado por LAP LAMBERT Academic Publishing, 2018
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abbas AdnanI am Adnan Abbas, got my Master degree in Accounting from Harbin University of Science and Technology, China. I am currently working on patterns of trade credit supply and demand in developing countries.This research s.
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Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2016
ISBN 10: 3662511886 ISBN 13: 9783662511886
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Outstanding doctoral thesis nominated for a Springer Theses Prize by Karlsruhe Institute of Technology, GermanyThis work is a key step towards a realistic GNSS stochastic model, and provides good examples of statistical verification and physical i.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg Sep 2016, 2016
ISBN 10: 3662511886 ISBN 13: 9783662511886
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 356 pp. Englisch.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg Jul 2013, 2013
ISBN 10: 3642348351 ISBN 13: 9783642348358
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 356 pp. Englisch.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2013
ISBN 10: 3642348351 ISBN 13: 9783642348358
Librería: moluna, Greven, Alemania
EUR 136,16
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Outstanding doctoral thesis nominated for a Springer Theses Prize by Karlsruhe Institute of Technology, GermanyThis work is a key step towards a realistic GNSS stochastic model, and provides good examples of statistical verification and physical i.
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Añadir al carritoCondición: New. Print on Demand pp. 331.
Idioma: Inglés
Publicado por Springer, Springer Jul 2013, 2013
ISBN 10: 3642348351 ISBN 13: 9783642348358
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 356 pp. Englisch.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 331.
Idioma: Inglés
Publicado por Springer, Springer Sep 2016, 2016
ISBN 10: 3662511886 ISBN 13: 9783662511886
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 160,49
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 356 pp. Englisch.
Librería: moluna, Greven, Alemania
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Añadir al carritoKartoniert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abbas AdnanIch bin Adnan Abbas und habe meinen Master-Abschluss in Rechnungswesen an der Harbin University of Science and Technology, China, gemacht. Derzeit beschaeftige ich mich mit den Mustern von Angebot und Nachfrage bei Handelsk.