• DocumentCode
    2837164
  • Title

    Target tracking algorithm using Gaussian cost-reference particle filter in WSN based on multi-modality information

  • Author

    Zhang, Jian ; Wu, Chengdong ; Jia, Zixi ; Wang, Tianbao

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2010
  • fDate
    26-28 May 2010
  • Firstpage
    1388
  • Lastpage
    1392
  • Abstract
    Target tracking algorithm using Gaussian cost-reference particle filter in WSN based on multi-modality information is proposed in this paper. Compared with WSN relying on sensors of single modality, two different nodes organize the network; Contrary to traditional particle filter algorithm for target tracking, this algorithm does not assume explicit mathematical models of the noise probabilistic distributions, but approximate posterior probability distribution of the state using Gaussian distribution. The mean and variance of Gaussian distribution as information interacted between nodes only need to be transmitted. Simulation results show that the algorithm can satisfy the need of a tracking accuracy and efficiently prolong the network lifetime.
  • Keywords
    Gaussian distribution; Gaussian processes; particle filtering (numerical methods); target tracking; wireless sensor networks; Gaussian cost reference particle filter; Gaussian distribution; WSN; approximate posterior probability distribution; multimodality information; noise probabilistic distribution; target tracking algorithm; wireless sensor network; Acoustic sensors; Energy consumption; Gaussian distribution; Infrared sensors; Magnetic sensors; Particle filters; Probability distribution; Sensor phenomena and characterization; Target tracking; Wireless sensor networks; Gaussian Cost-Reference Particle Filter; Multi-Modality; Target Tracking; Wireless Sensor Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2010 Chinese
  • Conference_Location
    Xuzhou
  • Print_ISBN
    978-1-4244-5181-4
  • Electronic_ISBN
    978-1-4244-5182-1
  • Type

    conf

  • DOI
    10.1109/CCDC.2010.5498195
  • Filename
    5498195