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Author: Xiaoguang Luo Publisher: Springer Science & Business Media ISBN: 364234836X Category : Technology & Engineering Languages : en Pages : 345
Book Description
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.
Author: Xiaoguang Luo Publisher: Springer Science & Business Media ISBN: 364234836X Category : Technology & Engineering Languages : en Pages : 345
Book Description
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.
Author: Jinling Wang Publisher: ISBN: Category : Languages : en Pages : 342
Book Description
(b)A stochastic modelling procedure for use in static positioning has been proposed, directly estimating the elements of the measurement covariance matrix. With this new procedure, reliability and efficiency of the positioning results can be improved; (c)A real-time stochastic modelling procedure for kinematic positioning has been developed, which uses the measurement filtering residuals to adaptively estimate the covariance matrix. The proposed procedure can significantly improve the reliability of ambiguity resolution in precise real-time positioning.
Author: Professor Gregoire Mariethoz Publisher: John Wiley & Sons ISBN: 111866275X Category : Science Languages : en Pages : 376
Book Description
This book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable reference for students, researchers and practitioners of all areas of the Earth Sciences where forecasting based on spatio-temporal data is performed.
Author: Jasper van Loon Publisher: ISBN: Category : Gravitational fields Languages : en Pages : 252
Book Description
Contents 1. Introduction 1 2. Estimation of the Earth's gravity field 9 3. Augmentation of the functional model 35 4. Stochastic model validation 49 5. Monte Carlo implementation 83 6. Outlier detection and robust estimation 97 7. Application 1: CHAMP satellite gravity data 115 8. Application 2: Joint inversion of global GPS time-series with GRACE gravity models 141 9. Application 3: Temporal aliasing of hydrological signals in a simulated GRACE recovery 165 10. Application 4: The computation of a height reference surface in Switzerland 177 11. Conclusions and recommendations 191 References 197 A. Series expansion into spherical harmonics 217 B. Matrix algebra and matrix analysis 219 C. Some standard distributions 221 Summary 223 Samenvatting 227 Curriculum Vitae 231
Author: Frank Neitzel Publisher: MDPI ISBN: 3039439812 Category : Technology & Engineering Languages : en Pages : 200
Book Description
In geodesy and geoinformation science, as well as in many other technical disciplines, it is often not possible to directly determine the desired target quantities. Therefore, the unknown parameters must be linked with the measured values by a mathematical model which consists of the functional and the stochastic models. The functional model describes the geometrical–physical relationship between the measurements and the unknown parameters. This relationship is sufficiently well known for most applications. With regard to the stochastic model, two problem domains of fundamental importance arise: 1. How can stochastic models be set up as realistically as possible for the various geodetic observation methods and sensor systems? 2. How can the stochastic information be adequately considered in appropriate least squares adjustment models? Further questions include the interpretation of the stochastic properties of the computed target values with regard to precision and reliability and the use of the results for the detection of outliers in the input data (measurements). In this Special Issue, current research results on these general questions are presented in ten peer-reviewed articles. The basic findings can be applied to all technical scientific fields where measurements are used for the determination of parameters to describe geometric or physical phenomena.
Author: Mariano J Valderrama Bonnet Publisher: World Scientific ISBN: 9814550701 Category : Languages : en Pages : 326
Book Description
This volume contains a selection of papers on recent developments in fields such as stochastic processes, multivariate data analysis and stochastic models in operations research, earth and life sciences and information theory, from an applicative perspective. Some of them have been extracted from lectures given at the Department of Statistics and Operations Research at the University of Granada for the past two years (Kai Lai Chung and Marcel F Neuts, among others). All the papers have been carefully selected and revised.
Author: Salvatore Nardi Publisher: ISBN: 9781423563600 Category : Global Positioning System Languages : en Pages : 144
Book Description
This thesis is concerned with the development of new closed form GPS position determination algorithms that work in the presence of pseudorange measurement noise. The mathematical derivation of two closed form algorithms, based on stochastic modeling and estimation techniques, is presented. The algorithms provide an estimate of the GPS solution parameters (viz., the user position and the user clock bias) as well as the estimation error covariance. The experimental results are analyzed by comparison to the baseline results from the conventional Iterative Least Squares (ILS) algorithm. In typical GPS scenarios, the closed form algorithms are extremely sensitive to noise, making them unsuitable for stand-alone use; however, they perform very well at estimating horizontal position parameters in ground-based pseudolite planar array scenarios where the ILS algorithm breaks down due to poor geometry. For typical scenarios, the use of a supplementary algorithm is required to refine the solution. Thus, the derivation of two supplementary algorithms is presented; the first based on a maximum likelihood approach and the second uses a Kalman like update approach. Both supplementary algorithms produce results comparable to the ILS results, but the Kalman update approach is preferred. The advantages introduced by the closed form, supplemented by the Kalman update, algorithm are: (1) The capability to estimate its estimation error covariance, and (2) The potential for computational efficiency due to the closed form nature of the solution.
Author: Xiaoguang Luo
Author: Xiaoguang Luo
Author: Christopher Ryan Keenan
Author: Jinling Wang
Author: Professor Gregoire Mariethoz
Author: Jasper van Loon
Author: Frank Neitzel
Author: AliReza Amiri-Simkooei
Author: Mariano J Valderrama Bonnet
Author: Frank Kleijer
Author: Salvatore Nardi