• DocumentCode
    3427401
  • Title

    SVM-based target tracking in combined with Sensor Scheduling

  • Author

    Liqun Shan ; Wang, Jinkuan ; Zhigang Liu ; Du, Ruiyan

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • Volume
    2
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Abstract
    A new target tracking method is presented to improve target location accuracy in the case of prolonging the network lifetime. The presented method utilizes sensor scheduling to extend the network lifetime and support vector machine for target tracking. Analysis and simulation results show that the algorithm has a high target localization accuracy by comparing with the least-square location method.
  • Keywords
    least squares approximations; scheduling; support vector machines; target tracking; wireless sensor networks; SVM-based target tracking; improve target location accuracy; least-square location method; network lifetime; sensor scheduling; support vector machine; Batteries; Broadcasting; Computer networks; Intelligent sensors; Scheduling; Sleep; Support vector machine classification; Support vector machines; Target tracking; Wireless sensor networks; classification; sensor scheduling; support vector machine (SVM); target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Design and Applications (ICCDA), 2010 International Conference on
  • Conference_Location
    Qinhuangdao
  • Print_ISBN
    978-1-4244-7164-5
  • Electronic_ISBN
    978-1-4244-7164-5
  • Type

    conf

  • DOI
    10.1109/ICCDA.2010.5541272
  • Filename
    5541272