• DocumentCode
    484933
  • Title

    Mobile Target Localization Based on Mean Shift in Wireless Sensor Networks

  • Author

    Luo, Haiyong ; Li, Jintao ; Zhao, Fang ; Lin, Yiming ; Zhu, Zhenmin

  • Author_Institution
    Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing
  • Volume
    1
  • fYear
    2008
  • fDate
    6-8 Oct. 2008
  • Firstpage
    248
  • Lastpage
    253
  • Abstract
    In order to localize the mobile targets in real time and with high accuracy, by employing mean shift algorithm to generate the proposal distribution for the joint particle filter, this paper proposes a novel mobile target localization algorithm, which we called mean shift particle filter. The mean shift particle filter algorithm significantly improves the accuracy of the particle state estimation and reduces the necessary number of samples by using the current observations in sampling procedure to obtain a sample distribution. It also reduces the interference among multiple targets in close proximity by weighting samples according to the virtual hamming distances and interaction potentials. By arranging the state distributions of mobile targets, the proposed scheme can handle the multiple peaks in state estimation of mobile targets and improves the localization accuracy.
  • Keywords
    radio direction-finding; state estimation; target tracking; tracking filters; wireless sensor networks; interference reduction; mean shift algorithm; mean shift particle filter; mobile target localization; particle state estimation; state distribution; virtual hamming distance; wireless sensor network; Distributed computing; Interference; Mobile computing; Particle filters; Particle tracking; Proposals; Sampling methods; State estimation; Target tracking; Wireless sensor networks; mean shift; particle filter; target localization; wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
  • Conference_Location
    Alexandria
  • Print_ISBN
    978-1-4244-2020-9
  • Electronic_ISBN
    978-1-4244-2021-6
  • Type

    conf

  • DOI
    10.1109/ICPCA.2008.4783586
  • Filename
    4783586