• DocumentCode
    2073235
  • Title

    Robust wireless multihop localization using mobile anchors

  • Author

    Ibrahim, Walid M. ; Taha, Abd-Elhamid M. ; Hassanein, Hossam S.

  • Author_Institution
    Sch. of Comput., Queen´s Univ., Kingston, ON, Canada
  • fYear
    2013
  • fDate
    9-13 June 2013
  • Firstpage
    1506
  • Lastpage
    1511
  • Abstract
    Knowing the position of sensor nodes in an environmental monitoring is useful to identify the location of events. However deploying GPS receivers or other anchor sensors is expensive, since the role of anchor nodes ends after localizing sensor nodes´ positions and they are transferred into ordinary sensor nodes. In this paper, we introduce a new localization scheme for a wireless sensor network that can localize sensor nodes using a collinear and non-collinear mobile anchor node. This scheme benefits from the estimated distance between neighbor nodes and additional information provided by the anchor node about the flow direction of the message. Each node localizes it´s position from two independent directions. A Kalman Filter is then used to improve the location accuracy for each node. Through simulation studies, we show that the scheme using a Kalman Filter decreases the estimation errors than using single direction by 31% and 16% better than using weighted averages. As well, our new scheme overcomes the collinearity problem that appears from using mobile anchor nodes.
  • Keywords
    Global Positioning System; Kalman filters; estimation theory; wireless sensor networks; GPS receivers; Kalman filter; anchor sensors; collinearity problem; environmental monitoring; estimated distance; estimation errors; flow direction; localization scheme; localize sensor nodes; location accuracy; mobile anchor nodes; mobile anchors; noncollinear mobile anchor node; ordinary sensor nodes; robust wireless multihop localization; sensor node positions; wireless sensor network; Covariance matrices; Equations; Estimation; Kalman filters; Mathematical model; Mobile communication; Tin; Collinearity; Flip Ambiguity; Kalman Filter; Localization; Mobile Anchor; Multihop; Positioning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2013 IEEE International Conference on
  • Conference_Location
    Budapest
  • ISSN
    1550-3607
  • Type

    conf

  • DOI
    10.1109/ICC.2013.6654726
  • Filename
    6654726