Analysis of opportunistic localization algorithms based on the linear matrix inequality method

  • Authors:
  • Francesco Zorzi;Andrea Bardella;Tanguy Pérennou;Guodong Kang;Andrea Zanella

  • Affiliations:
  • Università degli Studi di Padova, Italy;Università degli Studi di Padova, Italy;Université de Toulouse, France;Université de Toulouse, France and Northwestern Polytechnical University, Xi'an, China;Università degli Studi di Padova, Italy

  • Venue:
  • MobiOpp '10 Proceedings of the Second International Workshop on Mobile Opportunistic Networking
  • Year:
  • 2010

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Abstract

With the increasing spread of use of mobile devices there is a growing demand for location-aware services in a wide variety of contexts. Yet providing an accurate location estimation is difficult when considering cheap off-the-shelf mobile devices, particularly in indoors or urban environments. In this paper we define and compare different localization algorithms based on an opportunistic paradigm. In particular, we focus on range-free and range-based localization techniques that are based on the solution of a Linear Matrix Inequalities (LMI) problem. The performance achievable with this approach is analyzed in different scenarios, through extensive simulation campaign. Results show that LMI-based schemes, especially the range-based one, are potentially capable of yielding very accurate localization even after a limited number of opportunistic exchange, though performance is rather sensitive to the accuracy of the other nodes' self-localization and to the randomness of the radio channel.