A Dynamic UKF-Based UWB/Wheel Odometry Tightly Coupled Approach for Indoor Positioning

Liu, A; Wang, J; Lin, S; Kong, X

A Dynamic UKF-Based UWB/Wheel Odometry Tightly Coupled Approach for Indoor Positioning

Liu, A Wang, J

Lin, S Kong, X

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Electronics (Switzerland), 2024, 13, (8)
Issue Date:: 2024-04-01

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Field	Value	Language
dc.contributor.author	Liu, A
dc.contributor.author	Wang, J https://orcid.org/0000-0002-6282-0456
dc.contributor.author	Lin, S
dc.contributor.author	Kong, X
dc.date.accessioned	2025-01-03T03:23:31Z
dc.date.available	2025-01-03T03:23:31Z
dc.date.issued	2024-04-01
dc.identifier.citation	Electronics (Switzerland), 2024, 13, (8)
dc.identifier.issn	1450-5843
dc.identifier.issn	2079-9292
dc.identifier.uri	http://hdl.handle.net/10453/182949
dc.description.abstract	The centimetre-level accuracy of Ultra-wideband (UWB) has attracted significant attention in indoor positioning. However, the precision of UWB positioning is severely compromised by non-line-of-sight (NLOS) conditions that arise from complex indoor environments. On the other hand, odometry is widely applicable to wheeled robots due to its reliable short-term accuracy and high sampling frequency, but it suffers from long-term drift. This paper proposes a tightly coupled fusion method with a Dynamic Unscented Kalman Filter (DUKF), which utilises odometry to identify and mitigate NLOS effects on UWB measurements. Horizontal Dilution of Precision (HDOP) was introduced to assess the impact of geometric distribution between robots and UWB anchors on UWB positioning accuracy. By dynamically adjusting UKF parameters based on NLOS condition, HDOP values, and robot motion status, the proposed method achieves excellent UWB positioning results in a severe NLOS environment, which enables UWB positioning even when only one line-of-sight (LOS) UWB anchor is available. Experimental results under severe NLOS conditions demonstrate that the proposed system achieves a Root Mean Square Error (RMSE) of approximately 7.5 cm.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Electronics (Switzerland)
dc.relation.isbasedon	10.3390/electronics13081518
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.title	A Dynamic UKF-Based UWB/Wheel Odometry Tightly Coupled Approach for Indoor Positioning
dc.type	Journal Article
utslib.citation.volume	13
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Centre for Advanced Modelling and Geospatial lnformation Systems (CAMGIS)
pubs.organisational-group	University of Technology Sydney/UTS Groups/Centre for Built Infrastructure Resilience (CBIR)
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2025-01-03T03:23:29Z
pubs.issue	8
pubs.publication-status	Published
pubs.volume	13
utslib.citation.issue	8

Abstract:

The centimetre-level accuracy of Ultra-wideband (UWB) has attracted significant attention in indoor positioning. However, the precision of UWB positioning is severely compromised by non-line-of-sight (NLOS) conditions that arise from complex indoor environments. On the other hand, odometry is widely applicable to wheeled robots due to its reliable short-term accuracy and high sampling frequency, but it suffers from long-term drift. This paper proposes a tightly coupled fusion method with a Dynamic Unscented Kalman Filter (DUKF), which utilises odometry to identify and mitigate NLOS effects on UWB measurements. Horizontal Dilution of Precision (HDOP) was introduced to assess the impact of geometric distribution between robots and UWB anchors on UWB positioning accuracy. By dynamically adjusting UKF parameters based on NLOS condition, HDOP values, and robot motion status, the proposed method achieves excellent UWB positioning results in a severe NLOS environment, which enables UWB positioning even when only one line-of-sight (LOS) UWB anchor is available. Experimental results under severe NLOS conditions demonstrate that the proposed system achieves a Root Mean Square Error (RMSE) of approximately 7.5 cm.

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http://hdl.handle.net/10453/182949