• DocumentCode
    3582803
  • Title

    Side localization to increase localization accuracy

  • Author

    Ibrahim, Walid M. ; Abu Ali, Najah A. ; Taha, Abd-Elhamid M. ; Hassanein, Hossam S.

  • Author_Institution
    Sch. of Comput., Queen´s Univ., Kingston, ON, Canada
  • fYear
    2014
  • Firstpage
    810
  • Lastpage
    816
  • Abstract
    Estimating the location of sensor nodes in wireless sensor networks is a fundamental requirement in a variety of sensing applications. In large scale dense deployments where the area covered by sensor nodes is very large, it is impossible to localize all sensor nodes using single-hop localization techniques. A solution to this problem is to use a multi-hop localization technique to estimate sensor node positions. In some deployments it is required to maintain the anchor nodes at the edge of the simulated area. In previous work, we introduced a new localization scheme that uses distance measurements to localize sensor nodes using a collinear and non-collinear mobile anchor nodes placed at the edge of the sensed area. A Kalman Filter was then used to improve the location accuracy for each node. In this scheme each SN estimated its location from two independent directions then use such information to improve localization accuracy. In this paper, we extend the work to use side localization using hop measurements and fixed anchor node. We also compare the performance of using side localization for both hop and distance measurement. Through simulation we show that side localization using distance and hop measurements outperform DV-Hop and DV-Distance, which are mainstream localization protocols. The weighted mean hop measurement gives higher localization accuracy than using using distance measurement. However, if Kalman Filter is used distance measurement gives better localization accuracy.
  • Keywords
    Kalman filters; distance measurement; sensor placement; wireless sensor networks; Kalman filter; distance measurements; fixed anchor node; large scale dense deployments; mainstream localization protocols; multihop localization technique; noncollinear mobile anchor nodes; sensing applications; sensor node location; sensor node positions; side localization; single-hop localization techniques; weighted mean hop measurement; wireless sensor networks; Accuracy; Covariance matrices; Distance measurement; Estimation; Kalman filters; Mathematical model; Tin; Collinearity; Flip Ambiguity; Kalman Filter; Localization; Multihop; Positioning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications (AICCSA), 2014 IEEE/ACS 11th International Conference on
  • Type

    conf

  • DOI
    10.1109/AICCSA.2014.7073284
  • Filename
    7073284