Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/73634
Título: Fusion of channel state information and received signal strength for indoor localization using a single access point
Autores/as: Sánchez-Rodríguez, David 
Quintana-Suárez, Miguel A. 
Alonso-González, Itziar 
Ley-Bosch, Carlos 
Sánchez-Medina, Javier J. 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Amplitude processing
Channel state information
Features fusion
Fingerprinting
Indoor localization, et al.
Fecha de publicación: 2020
Proyectos: Enruta: Entorno de Localización de Alta Precisión Para Un Turismo Accesible 
Sistema de Localización Aplicado A Personas Con Diversidad Funcional. Posicionamiento y Predicción de Intenciones. 
Publicación seriada: Remote Sensing 
Resumen: In recent years, indoor localization systems based on fingerprinting have had significant advances yielding high accuracies. Those approaches often use information about channel communication, such as channel state information (CSI) and received signal strength (RSS). Nevertheless, these features have always been employed separately. Although CSI provides more fine-grained physical layer information than RSS, in this manuscript, a methodology for indoor localization fusing both features from a single access point is proposed to provide a better accuracy. In addition, CSI amplitude information is processed to remove high variability information that can negatively influence location estimation. The methodology was implemented and validated in two scenarios using a single access point located in two different positions and configured in 2.4 and 5 GHz frequency bands. The experiments show that the methodology yields an average error distance of about 0.1 m using the 5 GHz band and a single access point.
URI: http://hdl.handle.net/10553/73634
ISSN: 2072-4292
DOI: 10.3390/rs12121995
Fuente: Remote Sensing [EISSN 2072-4292], v. 12 (12), (Junio 2020)
Colección:Artículos
miniatura
PDF
Adobe PDF (3,62 MB)
Vista completa

Citas SCOPUSTM   

11
actualizado el 10-nov-2024

Citas de WEB OF SCIENCETM
Citations

9
actualizado el 10-nov-2024

Visitas

156
actualizado el 15-jun-2024

Descargas

132
actualizado el 15-jun-2024

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.