Robust Localization for Mobile Targets Along a Narrow Path with LoS/NLoS Interference

He, WN; Huang, XL; Xu, Z; Hu, F; Yu, S

Robust Localization for Mobile Targets Along a Narrow Path with LoS/NLoS Interference

He, WN Huang, XL Xu, Z Hu, F Yu, S

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Internet of Things Journal, 2024, 11, (11), pp. 20853-20866
Issue Date:: 2024-06-01

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Field	Value	Language
dc.contributor.author	He, WN
dc.contributor.author	Huang, XL
dc.contributor.author	Xu, Z
dc.contributor.author	Hu, F
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2024-08-07T05:02:52Z
dc.date.available	2024-08-07T05:02:52Z
dc.date.issued	2024-06-01
dc.identifier.citation	IEEE Internet of Things Journal, 2024, 11, (11), pp. 20853-20866
dc.identifier.issn	2372-2541
dc.identifier.issn	2327-4662
dc.identifier.uri	http://hdl.handle.net/10453/180263
dc.description.abstract	Recently, with the development of automatic driving, high-precision localization has become indispensable for safety. The inertial measurement unit (IMU) integrated with an ultrawideband (UWB) technology has been thought as a promising scheme by the company Humatics for trains. Generally, the spaces of transportation are extended along a long path with flexural tunnels and sideway obstacles around, where Nonline-of-Sight (NLoS) propagation happens frequently. However, a large interval deployment of UWB anchors along such a narrow path with NLoS interference will dramatically decrease localization performance. Hence, we propose a robust algorithm to mitigate the NLoS interference. First, a joint LoS/NLoS detection and mitigation algorithm is proposed to improve the ranging accuracy of mobile target with UWB tags under mixed LoS/NLoS interference. Second, we improve the conventional Kalman Filter (KF) algorithm with forward-backward propagation to integrate temporal correlations further. Finally, a comprehensive fusion localization scheme with ranging error mitigation and improved KF is proposed. The simulation results show that, regarding the static localization, the proposed joint LoS/NLoS detection and mitigation algorithm outperforms five other typical NLoS elimination algorithms, and achieves 48.2%, 62.4%, 45.5%, 69.9%, and 50.2% gains in terms of root mean square error (RMSE), under NLoS scenarios with a mean ranging error of 0.5 m. Regarding the dynamic localization, compared with two other typical KF localization algorithms, the proposed localization scheme achieves 20.9% and 14.5% localization accuracy improvements in LoS scenarios, 45.7% and 47.2% improvements in mixed LoS/NLoS scenarios, respectively. Furthermore, the effectiveness of the proposed scheme is also verified in our testing platform.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Internet of Things Journal
dc.relation.isbasedon	10.1109/JIOT.2024.3373795
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0805 Distributed Computing, 1005 Communications Technologies
dc.subject.classification	40 Engineering
dc.subject.classification	46 Information and computing sciences
dc.title	Robust Localization for Mobile Targets Along a Narrow Path with LoS/NLoS Interference
dc.type	Journal Article
utslib.citation.volume	11
utslib.for	0805 Distributed Computing
utslib.for	1005 Communications Technologies
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 Computer Science
pubs.organisational-group	University of Technology Sydney/Strength - CCSP - Centre for Cyber Security and Privacy
utslib.copyright.status	recently_added	*
dc.date.updated	2024-08-07T05:02:49Z
pubs.issue	11
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	11

Abstract:

Recently, with the development of automatic driving, high-precision localization has become indispensable for safety. The inertial measurement unit (IMU) integrated with an ultrawideband (UWB) technology has been thought as a promising scheme by the company Humatics for trains. Generally, the spaces of transportation are extended along a long path with flexural tunnels and sideway obstacles around, where Nonline-of-Sight (NLoS) propagation happens frequently. However, a large interval deployment of UWB anchors along such a narrow path with NLoS interference will dramatically decrease localization performance. Hence, we propose a robust algorithm to mitigate the NLoS interference. First, a joint LoS/NLoS detection and mitigation algorithm is proposed to improve the ranging accuracy of mobile target with UWB tags under mixed LoS/NLoS interference. Second, we improve the conventional Kalman Filter (KF) algorithm with forward-backward propagation to integrate temporal correlations further. Finally, a comprehensive fusion localization scheme with ranging error mitigation and improved KF is proposed. The simulation results show that, regarding the static localization, the proposed joint LoS/NLoS detection and mitigation algorithm outperforms five other typical NLoS elimination algorithms, and achieves 48.2%, 62.4%, 45.5%, 69.9%, and 50.2% gains in terms of root mean square error (RMSE), under NLoS scenarios with a mean ranging error of 0.5 m. Regarding the dynamic localization, compared with two other typical KF localization algorithms, the proposed localization scheme achieves 20.9% and 14.5% localization accuracy improvements in LoS scenarios, 45.7% and 47.2% improvements in mixed LoS/NLoS scenarios, respectively. Furthermore, the effectiveness of the proposed scheme is also verified in our testing platform.

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

http://hdl.handle.net/10453/180263