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Pré-Publication, Document De Travail Année : 2010

Analysis of Opportunistic Localization Algorithms Based on the Linear Matrix Inequality Method

Résumé

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.
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Dates et versions

hal-00452360 , version 1 (02-02-2010)
hal-00452360 , version 2 (03-02-2010)

Identifiants

  • HAL Id : hal-00452360 , version 1

Citer

Francesco Zorzi, Andrea Bardella, Guodong Kang, Tanguy Pérennou, Andrea Zanella. Analysis of Opportunistic Localization Algorithms Based on the Linear Matrix Inequality Method. 2010. ⟨hal-00452360v1⟩
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