A Novel Algorithm Modelling for UWB Localization Accuracy in Remote Sensing

Yu, Z; Chaczko, Z; Shi, J

A Novel Algorithm Modelling for UWB Localization Accuracy in Remote Sensing

Yu, Z

Chaczko, Z

Shi, J

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Remote Sensing, 2022, 14, (19)
Issue Date:: 2022-10-01

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Field	Value	Language
dc.contributor.author	Yu, Z https://orcid.org/0000-0002-8888-4570
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510
dc.contributor.author	Shi, J
dc.date.accessioned	2023-01-31T11:29:42Z
dc.date.available	2023-01-31T11:29:42Z
dc.date.issued	2022-10-01
dc.identifier.citation	Remote Sensing, 2022, 14, (19)
dc.identifier.issn	2072-4292
dc.identifier.issn	2072-4292
dc.identifier.uri	http://hdl.handle.net/10453/165694
dc.description.abstract	At present, the ultra-wideband (UWB) technology plays a vital role in the environment of indoor localization. As a new technology of wireless communications, UWB has many advantages, such as high accuracy, strong anti-multipath ability, and high transmission rate. However, in real-time operation, the accuracy of UWB is reduced by multi-sensor interference, antenna variations and system operation noise. We have developed a novel error modelling based on the curve fitted Kalman filter (CFKF) algorithm to solve these issues. This paper involves investigating and developing the error modelling algorithm that can calibrate the signal sensors, reduce the errors, and mitigate noise levels and interference signals. As part of the research investigation, a range of experiments was executed to validate the CFKF error modelling approach’s accuracy, reliability and viability. The experimental results indicate that this novel approach significantly improves the accuracy and precision of beacon-based localization. Validation tests also show that the CFKF error modelling method can improve the localization accuracy of UWB-based solutions.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Remote Sensing
dc.relation.isbasedon	10.3390/rs14194902
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0203 Classical Physics, 0406 Physical Geography and Environmental Geoscience, 0909 Geomatic Engineering
dc.title	A Novel Algorithm Modelling for UWB Localization Accuracy in Remote Sensing
dc.type	Journal Article
utslib.citation.volume	14
utslib.for	0203 Classical Physics
utslib.for	0406 Physical Geography and Environmental Geoscience
utslib.for	0909 Geomatic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Corporate Services)
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
dc.date.updated	2023-01-31T11:29:33Z
pubs.issue	19
pubs.publication-status	Published
pubs.volume	14
utslib.citation.issue	19

Abstract:

At present, the ultra-wideband (UWB) technology plays a vital role in the environment of indoor localization. As a new technology of wireless communications, UWB has many advantages, such as high accuracy, strong anti-multipath ability, and high transmission rate. However, in real-time operation, the accuracy of UWB is reduced by multi-sensor interference, antenna variations and system operation noise. We have developed a novel error modelling based on the curve fitted Kalman filter (CFKF) algorithm to solve these issues. This paper involves investigating and developing the error modelling algorithm that can calibrate the signal sensors, reduce the errors, and mitigate noise levels and interference signals. As part of the research investigation, a range of experiments was executed to validate the CFKF error modelling approach’s accuracy, reliability and viability. The experimental results indicate that this novel approach significantly improves the accuracy and precision of beacon-based localization. Validation tests also show that the CFKF error modelling method can improve the localization accuracy of UWB-based solutions.

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http://hdl.handle.net/10453/165694