• DocumentCode
    3310853
  • Title

    Signal processing by particle filtering for binary sensor networks

  • Author

    Djuric, Peter M. ; Vemula, Mahesh ; Bugallo, Monica F.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Stony Brook Univ., NY, USA
  • fYear
    2004
  • fDate
    1-4 Aug. 2004
  • Firstpage
    263
  • Lastpage
    267
  • Abstract
    In a wireless sensor network, limited power, communication, and computational resources are the major constraints that have to be overcome for their successful deployment and utilization. Binary sensor networks are a class of networks that get around these constraints. There, the sensors transmit only a binary digit on the occurrence of the event of interest, and therefore, the signals that reach the fusion center of these networks are highly compressed and pose challenging problems for recovering the sensed information. We consider the problem of tracking a vehicle, which moves along a 2-dimensional space, by using a binary sensor network that fuses information by particle filtering.
  • Keywords
    Monte Carlo methods; nonlinear filters; sensor fusion; target tracking; wireless sensor networks; binary sensor networks; fusion center; nonlinear filters; particle filtering; sequential Monte Carlo methods; signal processing; target tracking; vehicle tracking; wireless sensor network; Computer networks; Fuses; Information filtering; Information filters; Intelligent sensors; Sensor fusion; Sensor phenomena and characterization; Signal processing; Target tracking; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing Workshop, 2004 and the 3rd IEEE Signal Processing Education Workshop. 2004 IEEE 11th
  • Print_ISBN
    0-7803-8434-2
  • Type

    conf

  • DOI
    10.1109/DSPWS.2004.1437955
  • Filename
    1437955