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Robust train localisation method based on advanced map matching measurement-augmented tightly-coupled GNSS/INS with error-state UKF

Liu, Dan and Jiang, Wei and Cai, Baigen and Heirich, Oliver and Wang, Jian and Wei, Shangguan (2023) Robust train localisation method based on advanced map matching measurement-augmented tightly-coupled GNSS/INS with error-state UKF. Journal of Navigation. Cambridge University Press. doi: 10.1017/S0373463323000097. ISSN 0373-4633.

Full text not available from this repository.

Official URL: https://doi.org/10.1017/S0373463323000097

Abstract

This paper presents a robust train localisation system by fusing a Global Navigation Satellite System (GNSS) with an Inertial Navigation System (INS) in a tightly-coupled (TC) strategy. To improve navigation performance in GNSS partly blocked areas, an advanced map-matching (MM) measurement-augmented TC GNSS/INS method is proposed via an error-state unscented Kalman filter (UKF). The advanced MM generates a matched position using a one-step predicted position from a UKF time update step with binary search algorithm and a point–line projection algorithm. The matched position inputs as an additional measurement to fuse with the INS position to augment the degraded GNSS pseudorange measurement to optimise the state estimation in the UKF measurement update step. Both the real train test on the Qinghai–Tibet railway and the simulation were carried out and the results confirm that the proposed advanced MM measurement-augmented TC GNSS/INS with error-state UKF provides the best horizontal positioning accuracy of 0 ⋅ 67 m, which performs an improvement of about 71% and 90% with respect to TC GNSS/INS with only error-state UKF and only error-state Extended Kalman filter in GNSS partly blocked areas.

Item URL in elib:https://elib.dlr.de/195107/
Document Type:Article
Title:Robust train localisation method based on advanced map matching measurement-augmented tightly-coupled GNSS/INS with error-state UKF
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Liu, DanSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaUNSPECIFIEDUNSPECIFIED
Jiang, WeiSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaUNSPECIFIEDUNSPECIFIED
Cai, BaigenSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaUNSPECIFIEDUNSPECIFIED
Heirich, OliverUNSPECIFIEDhttps://orcid.org/0000-0001-5191-5997UNSPECIFIED
Wang, JianSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaUNSPECIFIEDUNSPECIFIED
Wei, ShangguanSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaUNSPECIFIEDUNSPECIFIED
Date:15 May 2023
Journal or Publication Title:Journal of Navigation
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI:10.1017/S0373463323000097
Publisher:Cambridge University Press
ISSN:0373-4633
Status:Published
Keywords:Railway, GNSS, INS, tightly-coupled, UKF, Error state Kalman filter,
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Rail Transport
DLR - Research area:Transport
DLR - Program:V SC Schienenverkehr
DLR - Research theme (Project):V - TraCo - Train Control and Management
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation > Communications Systems
Deposited By: Heirich, Dr.-Ing. Oliver
Deposited On:01 Jun 2023 14:53
Last Modified:01 Jun 2023 14:53

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