Monte-Carlo Localization for Mobile Wireless Sensor Networks

  • Aline Baggio
  • Koen Langendoen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4325)

Abstract

Localization is crucial to many applications in wireless sensor networks. This article presents a range-free anchor-based localization algorithm for mobile wireless sensor networks that builds upon the Monte Carlo Localization algorithm. We improve the localization accuracy and efficiency by making better use of the information a sensor node gathers and by drawing the necessary location samples faster. Namely, we constrain the area from which samples are drawn by building a box that covers the region where anchors’ radio ranges overlap. Simulation results show that localization accuracy is improved by a minimum of 4% and by a maximum of 73%, on average 30%, for varying node speeds when considering nodes with knowledge of at least three anchors. The coverage is also strongly affected by speed and its improvement ranges from 3% to 55%, on average 22%. Finally, the processing time is reduced by 93% for a similar localization accuracy.

Keywords

Distributed localization algorithms wireless sensor net- works mobility Monte Carlo Localization simulations 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Aline Baggio
    • 1
  • Koen Langendoen
    • 1
  1. 1.Delft University of TechnologyThe Netherlands

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