Environment-Aware Regression for Indoor Localization based on WiFi Fingerprinting
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Environment-Aware Regression for Indoor Localization based on WiFi FingerprintingAutoria
Data de publicació
2021-04-19Editor
Institute of Electrical and Electronics Engineers; IEEEISSN
1530-437X; 1558-1748Cita bibliogràfica
MENDOZA-SILVA, Germán, et al. Environment-Aware Regression for Indoor Localization based on WiFi Fingerprinting. IEEE Sensors Journal, 2021.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7361Versió
info:eu-repo/semantics/acceptedVersionParaules clau / Matèries
Resum
Data enrichment through interpolation or regression is a common approach to deal with sample collection for Indoor Localization with WiFi fingerprinting. This paper provides guidelines on where to collect WiFi samples, ... [+]
Data enrichment through interpolation or regression is a common approach to deal with sample collection for Indoor Localization with WiFi fingerprinting. This paper provides guidelines on where to collect WiFi samples, and proposes a new model for received signal strength regression. The new model creates vectors that describe the presence of obstacles between an access point and the collected samples. The vectors, the distance between the access point and the positions of the samples, and the collected, are used to train a Support Vector Regression. The experiments included some relevant analyses and showed that the proposed model improves received signal strength regression in terms of regression residuals and positioning accuracy. [-]
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info:eu-repo/semantics/openAccess
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