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A Maximum Likelihood UWB Localization Algorithm Exploiting Knowledge of the Service Area Layout

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Abstract

In this paper a method for ultra-wideband (UWB) localization for indoor applications is proposed. Beacons at known locations exchange signals with a tag to the purpose of estimating its position from range measurements. These measurements are accurate only when the ray corresponding to the direct path (DP) from tag to beacon is strong enough. In an UWB indoor environment, however, the DP may be blocked by thick walls or metallic obstacles, giving rise to large range errors. Several methods are available to mitigate this problem, exploiting different degrees of prior information. Techniques exploiting range error models or based on traditional fingerprinting lead to better results than methods that do not require any prior knowledge. We propose a new method that combines the maximum likelihood principle with range error models and special fingerprints. Its performance, assessed by simulation and compared to other techniques, is shown to be superior to traditional fingerprinting in the presence of environmental changes.

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Authors and Affiliations

  1. Department of Signal Theory and Communications, University of Seville, Camino de los Descubrimientos s/n, 41092, Seville, Spain

    Eva Arias-de-Reyna

  2. Department of Information Engineering, University of Pisa, Via Caruso 16, 56122, Pisa, Italy

    Umberto Mengali

Authors
  1. Eva Arias-de-Reyna
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  2. Umberto Mengali
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Corresponding author

Correspondence to Eva Arias-de-Reyna.

Additional information

This work has been supported by the Spanish Government (Ministerio de Ciencia e Innovación, through the Projects CSD2008-00010 COMONSENS of the Consolider-Ingenio 2010 Program and TEC2009-14504-C02-02), by the European Union (FEDER) and by Junta de Andalucía (TIC-155).

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Arias-de-Reyna, E., Mengali, U. A Maximum Likelihood UWB Localization Algorithm Exploiting Knowledge of the Service Area Layout. Wireless Pers Commun 69, 1413–1426 (2013). https://doi.org/10.1007/s11277-012-0642-2

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  • DOI: https://doi.org/10.1007/s11277-012-0642-2

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