Probabilistic Time of Arrival Localization

Pérez Cruz, Fernando; Martínez Olmos, Pablo; Minyi Zhang, Michael; Huang, Howard

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dc.contributor.author	Pérez Cruz, Fernando
dc.contributor.author	Martínez Olmos, Pablo
dc.contributor.author	Minyi Zhang, Michael
dc.contributor.author	Huang, Howard
dc.date.accessioned	2021-05-25T08:56:47Z
dc.date.available	2021-05-25T08:56:47Z
dc.date.issued	2019-11
dc.identifier.bibliographicCitation	Perez-Cruz, F., Olmos, P. M., Zhang, M. M. & Huang, H. (2019). Probabilistic Time of Arrival Localization. IEEE Signal Processing Letters, 26(11), pp. 1683–1687.
dc.identifier.issn	1070-9908
dc.identifier.uri	http://hdl.handle.net/10016/32740
dc.description.abstract	In this letter, we take a new approach for time of arrival geo-localization. We show that the main sources of error in metropolitan areas are due to environmental imperfections that bias our solutions, and that we can rely on a probabilistic model to learn and compensate for them. The resulting localization error is validated using measurements from a live LTE cellular network to be less than 10 meters, representing an order-of-magnitude improvement.
dc.format.extent	5
dc.language.iso	eng
dc.publisher	IEEE
dc.rights	© 2019, IEEE
dc.subject.other	Probabilistic modeling
dc.subject.other	Time of arrival localization
dc.subject.other	Error compensation
dc.subject.other	Error statistics
dc.subject.other	Location based services
dc.subject.other	Long term evolution
dc.title	Probabilistic Time of Arrival Localization
dc.type	article
dc.subject.eciencia	Telecomunicaciones
dc.identifier.doi	https://doi.org/10.1109/LSP.2019.2944005
dc.rights.accessRights	openAccess
dc.relation.projectID	Gobierno de España. TEC2016-78434-C3-3-R
dc.relation.projectID	info:eu-repo/grantAgreement/EC/714161
dc.relation.projectID	Comunidad de Madrid. IND2017/TIC-7618
dc.relation.projectID	Comunidad de Madrid. IND2018/TIC-9649
dc.relation.projectID	Comunidad de Madrid. Y2018/TCS-4705
dc.type.version	acceptedVersion
dc.identifier.publicationfirstpage	1683
dc.identifier.publicationissue	11
dc.identifier.publicationlastpage	1687
dc.identifier.publicationtitle	IEEE Signal Processing Letters
dc.identifier.publicationvolume	26
dc.identifier.uxxi	AR/0000024434
dc.contributor.funder	Ministerio de Economía y Competitividad (España)
dc.contributor.funder	Comunidad de Madrid
dc.contributor.funder	European Commission
dc.affiliation.dpto	UC3M. Departamento de Teoría de la Señal y Comunicaciones
dc.affiliation.grupoinv	UC3M. Grupo de Investigación: Tratamiento de la Señal y Aprendizaje (GTSA)