| 書目名稱 | GPS Stochastic Modelling |
| 副標題 | Signal Quality Measu |
| 編輯 | Xiaoguang Luo |
| 視頻video | http://file.papertrans.cn/381/380158/380158.mp4 |
| 概述 | Outstanding doctoral thesis nominated for a Springer Theses Prize by Karlsruhe Institute of Technology, Germany.This work is a key step towards a realistic GNSS stochastic model, and provides good exa |
| 叢書名稱 | Springer Theses |
| 圖書封面 |  |
| 描述 | 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. . |
| 出版日期 | Book 2013 |
| 關鍵詞 | ARMA Process; AutoRegressive Moving Average Process; Hypothesis Testing; Signal-to-Noise Ratio (SNR); St |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-34836-5 |
| isbn_softcover | 978-3-662-51188-6 |
| isbn_ebook | 978-3-642-34836-5Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer-Verlag Berlin Heidelberg 2013 |
|Archiver|手機版|小黑屋|
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