Hybrid indoor localization system combining multilateration and fingerprinting

Oliveira, Leonardo Sestrem de; Rayel, Ohara; Leitão, Paulo

Publication

Hybrid indoor localization system combining multilateration and fingerprinting

2022Conference paper

dc.contributor.author	Oliveira, Leonardo Sestrem de
dc.contributor.author	Rayel, Ohara
dc.contributor.author	Leitão, Paulo
dc.date.accessioned	2023-03-06T15:43:10Z
dc.date.available	2023-03-06T15:43:10Z
dc.date.issued	2022
dc.description.abstract	Indoor localization systems enable object tracking, e.g., related to retail, logistics and mobile robotics during their life cycle. This paper describes a real-world scenario implementation, based on Bluetooth Low Energy (BLE) beacons, evaluating a hybrid indoor positioning system (H-IPS) that combines two RSSI-based approaches: Multilateration (MLT) and Fingerprinting (FP). In addition, a Kalman Filter (KF) was employed to decrease the positioning errors of both techniques. Furthermore a track-to-track fusion (TTF) is performed on the two KF outputs to maximize the performance. The results show that the accuracy of H-IPS overcomes the standalone FP in 21%, while the original MLT is outperformed in 52%. Finally, the proposed solution demonstrated a probability of error < 2 m of 80%, while the same probability for the FP and MLT were 56% and 20%, respectively.	pt_PT
dc.description.sponsorship	FCT – Fundação para a Ciência e Tecnologia within the Project Scope UIDB/05757/2020.
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	de Oliveira, Leonardo; Rayel, Ohara; Leitao, Paulo (2022). Hybrid indoor localization system combining multilatration and fingerprinting. In the 48th Annual Conference of the IEEE Industrial Electronics Society (IECON’22). Brussels. p. 1-6	pt_PT
dc.identifier.doi	10.1109/IECON49645.2022.9968816	pt_PT
dc.identifier.uri	http://hdl.handle.net/10198/27495
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	IEEE	pt_PT
dc.relation	Research Centre in Digitalization and Intelligent Robotics
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	pt_PT
dc.subject	Fingerprinting	pt_PT
dc.subject	Multilateration	pt_PT
dc.subject	Indoor positioning system	pt_PT
dc.subject	Kalman filtering	pt_PT
dc.subject	Sensor fusion	pt_PT
dc.subject	Bluetooth low energy	pt_PT
dc.title	Hybrid indoor localization system combining multilateration and fingerprinting	pt_PT
dc.type	conference paper
dspace.entity.type	Publication
oaire.awardTitle	Research Centre in Digitalization and Intelligent Robotics
oaire.awardURI	info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.citation.conferencePlace	Brussels	pt_PT
oaire.citation.endPage	6	pt_PT
oaire.citation.startPage	1	pt_PT
oaire.citation.title	the 48th Annual Conference of the IEEE Industrial Electronics Society (IECON’22)	pt_PT
oaire.fundingStream	6817 - DCRRNI ID
person.familyName	Oliveira
person.familyName	Leitão
person.givenName	Leonardo Sestrem de
person.givenName	Paulo
person.identifier	A-8390-2011
person.identifier.ciencia-id	6F18-DAD8-ACDC
person.identifier.ciencia-id	8316-8F13-DA71
person.identifier.orcid	0000-0002-9344-3075
person.identifier.orcid	0000-0002-2151-7944
person.identifier.scopus-author-id	35584388900
project.funder.identifier	http://doi.org/10.13039/501100001871
project.funder.name	Fundação para a Ciência e a Tecnologia
rcaap.rights	restrictedAccess	pt_PT
rcaap.type	conferenceObject	pt_PT
relation.isAuthorOfPublication	d39f1e66-56e1-472d-8897-969476357c9b
relation.isAuthorOfPublication	68d9eb25-ad4f-439b-aeb2-35e8708644cc
relation.isAuthorOfPublication.latestForDiscovery	d39f1e66-56e1-472d-8897-969476357c9b
relation.isProjectOfPublication	6e01ddc8-6a82-4131-bca6-84789fa234bd
relation.isProjectOfPublication.latestForDiscovery	6e01ddc8-6a82-4131-bca6-84789fa234bd