Ensembling Multiple Radio Maps with Dynamic Noise in Fingerprint-based Indoor Positioning
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/159451
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INVESTIGACIONMetadata
Title
Ensembling Multiple Radio Maps with Dynamic Noise in Fingerprint-based Indoor PositioningAuthor (s)
Date
2021-06-15Publisher
Institute of Electrical and Electronics Engineers; IEEEISBN
978-1-7281-8964-2Bibliographic citation
J. Torres-Sospedra et al., "Ensembling Multiple Radio Maps with Dynamic Noise in Fingerprint-based Indoor Positioning," 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 2021, pp. 1-5, doi: 10.1109/VTC2021-Spring51267.2021.9448947.Type
info:eu-repo/semantics/conferenceObjectPublisher version
https://ieeexplore.ieee.org/xpl/conhome/9448628/proceedingVersion
info:eu-repo/semantics/submittedVersionSubject
Abstract
Fingerprint-based indoor positioning is widely used
in many contexts, including pedestrian and autonomous vehicles
navigation. Many approaches have used traditional Machine
Learning models to deal with fingerprinting, ... [+]
Fingerprint-based indoor positioning is widely used
in many contexts, including pedestrian and autonomous vehicles
navigation. Many approaches have used traditional Machine
Learning models to deal with fingerprinting, being k-NN the
most common used one. However, the reference data (or radio
map) is generally limited, as data collection is a very demanding
task, which degrades overall accuracy. In this work, we propose
a novel approach to add random noise to the radio map which
will be used in combination with an ensemble model. Instead
of augmenting the radio map, we create n noisy versions of
the same size, i.e. our proposed Indoor Positioning model will
combine n estimations obtained by independent estimators built
with the n noisy radio maps. The empirical results have shown
that our proposed approach improves the baseline method results
in around 10% on average [-]
Description
Ponencia presentada en 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 25-28 April 2021
Funder Name
Ministerio de Ciencia, Innovación y Universidades (Spain) | Ministerio de Economía y Competitividad | European Union’s Horizon 2020 Research | Fundaçao para a Ciência e Tecnologia
Project code
PTQ2018-009981 | RTI2018-095168-B-C54 | TEC2017-90808-REDT | UIDB/00319/2020 | PD/BD/137401/2018
Investigation project
info:eu-repo/grantAgreement/EC/H2020/813278Rights
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess