Characterising kinematic positioning errors when using satellite based augmentation system

Fault detection and exclusion (FDE) is the main task for pre-processing of global navigation satellite system (GNSS) positions and is a fundamental process in integrity monitoring that is needed to achieve reliable positioning for applications such as in intelligent transport systems. A widely used...

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Main Authors: Khaki, Mehdi, El-Mowafy, Ahmed
Format: Journal Article
Published: Wydawnictwo Centrum Badan Kosmicznych 2020
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/79695
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author Khaki, Mehdi
El-Mowafy, Ahmed
author_facet Khaki, Mehdi
El-Mowafy, Ahmed
author_sort Khaki, Mehdi
building Curtin Institutional Repository
collection Online Access
description Fault detection and exclusion (FDE) is the main task for pre-processing of global navigation satellite system (GNSS) positions and is a fundamental process in integrity monitoring that is needed to achieve reliable positioning for applications such as in intelligent transport systems. A widely used method is the solution separation (SS) algorithm. The FDE in SS traditionally builds the models assuming positioning errors are normally distributed. However, in urban environments, this traditional assumption may no longer be valid. The objective of this study is to investigate this and further examine the performance of alternative distributions, which can be useful for FDE modelling and thus improved navigation. In particular, it investigates characterization of positioning errors using GNSS when the Australian satellite-based augmentation system (SBAS) test bed is used, which comprised different positioning modes, including single-point positioning (SPP) using the L1 global positioning system (GPS) legacy SBAS, the second-generation dual-frequency multi-constellation (DFMC) SBAS service for GPS and Galileo, and, finally, precise point positioning (PPP) using GPS and Galileo observations. Statistical analyses are carried out to study the position error distributions over different possible operational environments, including open sky, low-density urban environment, and high-density urban environment. Significant autocorrelation values are also found over all areas. This, however, is more evident for PPP solution. Furthermore, the applied distribution analyses applied suggest that in addition to the normal distribution, logistic, Weibull, and gamma distribution functions can fit the error data in various cases. This information can be used in building more representative FDE models according to the work environment.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-796952020-06-24T05:51:20Z Characterising kinematic positioning errors when using satellite based augmentation system Khaki, Mehdi El-Mowafy, Ahmed GNSS Kinematic Positioning Error characterisation SBAS 0909 - Geomatic Engineering Fault detection and exclusion (FDE) is the main task for pre-processing of global navigation satellite system (GNSS) positions and is a fundamental process in integrity monitoring that is needed to achieve reliable positioning for applications such as in intelligent transport systems. A widely used method is the solution separation (SS) algorithm. The FDE in SS traditionally builds the models assuming positioning errors are normally distributed. However, in urban environments, this traditional assumption may no longer be valid. The objective of this study is to investigate this and further examine the performance of alternative distributions, which can be useful for FDE modelling and thus improved navigation. In particular, it investigates characterization of positioning errors using GNSS when the Australian satellite-based augmentation system (SBAS) test bed is used, which comprised different positioning modes, including single-point positioning (SPP) using the L1 global positioning system (GPS) legacy SBAS, the second-generation dual-frequency multi-constellation (DFMC) SBAS service for GPS and Galileo, and, finally, precise point positioning (PPP) using GPS and Galileo observations. Statistical analyses are carried out to study the position error distributions over different possible operational environments, including open sky, low-density urban environment, and high-density urban environment. Significant autocorrelation values are also found over all areas. This, however, is more evident for PPP solution. Furthermore, the applied distribution analyses applied suggest that in addition to the normal distribution, logistic, Weibull, and gamma distribution functions can fit the error data in various cases. This information can be used in building more representative FDE models according to the work environment. 2020 Journal Article http://hdl.handle.net/20.500.11937/79695 10.2478/arsa-2020-0001 http://creativecommons.org/licenses/by-nc-nd/4.0 Wydawnictwo Centrum Badan Kosmicznych fulltext
spellingShingle GNSS
Kinematic Positioning
Error characterisation
SBAS
0909 - Geomatic Engineering
Khaki, Mehdi
El-Mowafy, Ahmed
Characterising kinematic positioning errors when using satellite based augmentation system
title Characterising kinematic positioning errors when using satellite based augmentation system
title_full Characterising kinematic positioning errors when using satellite based augmentation system
title_fullStr Characterising kinematic positioning errors when using satellite based augmentation system
title_full_unstemmed Characterising kinematic positioning errors when using satellite based augmentation system
title_short Characterising kinematic positioning errors when using satellite based augmentation system
title_sort characterising kinematic positioning errors when using satellite based augmentation system
topic GNSS
Kinematic Positioning
Error characterisation
SBAS
0909 - Geomatic Engineering
url http://hdl.handle.net/20.500.11937/79695