Situation Goodness Method for Weighted Centroid-Based Wi-Fi APs Localization

  • Germán M. Mendoza-Silva
  • Joaquín Torres-Sospedra
  • Joaquín Huerta
  • Raul Montoliu
  • Fernando Benítez
  • Oscar Belmonte
Conference paper
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


Knowing the location of Wi-Fi antennas may be critical for indoor localization. However, in a real environment, their positions may be unknown since they can be managed by external entities. This paper introduces a new method for evaluating the suitability of using the weighted centroid method for the 2D localization of a Wi-Fi AP. The method is based on the idea that the weighted centroid method provides its best results when there are fingerprints taken around the AP. In order to find the probability of being in the presence of such situations, a natural neighbor interpolation method is used to find the regions with the highest signal strengths. A geometrical method is then used to characterize that probability based on the distribution of those regions in relation to the AP position estimation given by the weighted centroid method. The paper describes the testing location and the used Wi-Fi fingerprints database. That database is used to create new databases that recreate different sampling possibilities through a samples deletion strategy. The original database and the newly created ones are then used to evaluate the localization results of several AP localization methods and the new method proposed in this paper. The evaluation results have shown that the proposed method is able to provide a proper probability for the suitability of using the weighted centroid method for localizing a Wi-Fi AP.


Indoor localization Wi-Fi aps localization Weighted centroid Interpolation LBS 



The authors gratefully acknowledge funding from the European Union through the GEO-C project (H2020-MSCA-ITN- 2014, Grant Agreement Number 642332, http://www.geo-ceu/).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Germán M. Mendoza-Silva
    • 1
  • Joaquín Torres-Sospedra
    • 1
  • Joaquín Huerta
    • 1
  • Raul Montoliu
    • 1
  • Fernando Benítez
    • 1
  • Oscar Belmonte
    • 1
  1. 1.Institute of New Imaging TechnologiesUniversitat Jaume I, AvdaCastellón de la PlanaSpain

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