Precise Indoor Positioning With Sensor Fusion of Ultra-Wideband and Odometer

Liu, Ang

Precise Indoor Positioning With Sensor Fusion of Ultra-Wideband and Odometer

Liu, Ang

Permalink

Publication Type:: Thesis
Issue Date:: 2025

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download thesisAdobe PDF (5.71 MB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Liu, Ang
dc.date.accessioned	2025-07-03T23:49:21Z
dc.date.available	2025-07-03T23:49:21Z
dc.date.issued	2025
dc.identifier.uri	http://hdl.handle.net/10453/188076
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	This research has developed a low-cost, high-precision indoor positioning system based on Ultra-wideband (UWB) and wheeled odometer fusion. The research consists of two main stages: UWB-only positioning and sensor fusion. The UWB-only stage focuses on identifying and mitigating Non-Line-of-Sight (NLOS) errors, which are the major factors affecting UWB positioning accuracy. A sliding-window algorithm has been proposed to identify 90% NLOS by observing the sudden change in the UWB-measured distances. An error modelling method is proposed to mitigate walls-caused NLOS errors based on walls' parameterisation and the incidence angle of UWB signals. Centimetre-level positioning accuracy is achieved when wall-caused NLOS errors are correctly identified and mitigated. The possibility of realising low-cost, large-scale UWB coverage is explored by moving UWB anchors. In the sensor fusion stage, UWB and odometer loose coupling is first applied to reach an RMSE of less than 10 cm in strong NLOS environments. A tight coupling method based on dynamic Unscented Kalman Filter (UKF) has been developed by adjusting UKF parameters dynamically to adapt to environmental changes for stable and accurate positioning. Experiments show that an RMSE of 8cm is achieved in a harsh indoor environment, even when there is only one anchor, but all others are NLOS.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/188076/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2025 Ang Liu
dc.rights	au.edu.uts.lib/cph
dc.title	Precise Indoor Positioning With Sensor Fusion of Ultra-Wideband and Odometer	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

This research has developed a low-cost, high-precision indoor positioning system based on Ultra-wideband (UWB) and wheeled odometer fusion. The research consists of two main stages: UWB-only positioning and sensor fusion. The UWB-only stage focuses on identifying and mitigating Non-Line-of-Sight (NLOS) errors, which are the major factors affecting UWB positioning accuracy. A sliding-window algorithm has been proposed to identify 90% NLOS by observing the sudden change in the UWB-measured distances. An error modelling method is proposed to mitigate walls-caused NLOS errors based on walls' parameterisation and the incidence angle of UWB signals. Centimetre-level positioning accuracy is achieved when wall-caused NLOS errors are correctly identified and mitigated. The possibility of realising low-cost, large-scale UWB coverage is explored by moving UWB anchors. In the sensor fusion stage, UWB and odometer loose coupling is first applied to reach an RMSE of less than 10 cm in strong NLOS environments. A tight coupling method based on dynamic Unscented Kalman Filter (UKF) has been developed by adjusting UKF parameters dynamically to adapt to environmental changes for stable and accurate positioning. Experiments show that an RMSE of 8cm is achieved in a harsh indoor environment, even when there is only one anchor, but all others are NLOS.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/188076