Dynamic chanel model LMS updating for RSS-based localization

Tarrío Alonso, Paula; Bernardos Barbolla, Ana M.; Xian, Wan y Casar Corredera, Jose Ramon (2011). Dynamic chanel model LMS updating for RSS-based localization. En: "6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011", 23/05/2011 - 25/05/2011, Wroclaw, Polonia. ISBN 978-3-642-21221-5.

Descripción

Título: Dynamic chanel model LMS updating for RSS-based localization
Autor/es:
  • Tarrío Alonso, Paula
  • Bernardos Barbolla, Ana M.
  • Xian, Wan
  • Casar Corredera, Jose Ramon
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011
Fechas del Evento: 23/05/2011 - 25/05/2011
Lugar del Evento: Wroclaw, Polonia
Título del Libro: Proceedings of he 6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011
Fecha: 2011
ISBN: 978-3-642-21221-5
Materias:
Palabras Clave Informales: Indoor localization, RSS, calibration, channel model, LMS
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Received signal strength-based localization systems usually rely on a calibration process that aims at characterizing the propagation channel. However, due to the changing environmental dynamics, the behavior of the channel may change after some time, thus, recalibration processes are necessary to maintain the positioning accuracy. This paper proposes a dynamic calibration method to initially calibrate and subsequently update the parameters of the propagation channel model using a Least Mean Squares approach. The method assumes that each anchor node in the localization infrastructure is characterized by its own propagation channel model. In practice, a set of sniffers is used to collect RSS samples, which will be used to automatically calibrate each channel model by iteratively minimizing the positioning error. The proposed method is validated through numerical simulation, showing that the positioning error of the mobile nodes is effectively reduced. Furthermore, the method has a very low computational cost; therefore it can be used in real-time operation for wireless resource-constrained nodes.

Más información

ID de Registro: 11637
Identificador DC: http://oa.upm.es/11637/
Identificador OAI: oai:oa.upm.es:11637
URL Oficial: http://hais.pwr.wroc.pl/
Depositado por: Memoria Investigacion
Depositado el: 05 Dic 2012 11:48
Ultima Modificación: 20 Abr 2016 19:39
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