Automatic virtual calibration of range-based indoor localization systems

  • Authors:

  • Paolo Barsocchi;Stefano Lenzi;Stefano Chessa;Francesco Furfari

  • Affiliations:

  • ISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, Italy;ISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, Italy;ISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, Italy and Computer Science Department, University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa, Italy;ISTI-CNR, Pisa Research Area, Via G.Moruzzi 1, 56124 Pisa, Italy

  • Venue:
  • Wireless Communications & Mobile Computing
  • Year:
  • 2012

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Abstract

The localization methods based on received signal strength indicator (RSSI) link the RSSI values to the position of the mobile to be located. In the RSSI localization techniques based on propagation models, the accuracy depends on the tuning of the propagation models parameters. In indoor wireless networks, the propagation conditions are hardly predictable due to the dynamic nature of the RSSI, and consequently the parameters of the propagation model may change. In this paper, we present an automatic virtual calibration method of the propagation model that does not require human intervention; therefore, can be periodically performed, following the wireless channel conditions. We also propose a novel RSSI-based localization algorithm that selects the RSSI values according to their strength, and uses a calibrated propagation model to transform these values into distances, in order to estimate the position of the mobile. Copyright © 2011 John Wiley & Sons, Ltd. (We propose an automatic calibration procedure of the signal propagation model that is only based on the RSSIs measured among the anchors and that can be executed periodically and automatically (i.e., without human intervention). Based on the virtual calibration procedure, we propose a localization algorithm that selects the anchors with higher signal strength, and it exploits the calibrated propagation model to relate RSSI measures with distances. Finally, in order to provide the mobile position, the algorithm uses a trilateration method.)