• DocumentCode
    1503175
  • Title

    Real-Time Estimation of Sensor Node´s Position Using Particle Swarm Optimization With Log-Barrier Constraint

  • Author

    Nguyen, Hong Anh ; Guo, Hao ; Low, Kay-Soon

  • Author_Institution
    Inst. of Infocomm Res., A*STAR, Singapore, Singapore
  • Volume
    60
  • Issue
    11
  • fYear
    2011
  • Firstpage
    3619
  • Lastpage
    3628
  • Abstract
    In this paper, a new approach is proposed to estimate the location of a sensor in a wireless sensor network. For the estimation, only a few anchor nodes with known locations and received signal strength (RSS) indicator (RSSI) are needed. It is well known that the RSS reduces with increasing distance between the transceivers following a nonlinear path loss model. Most published works determine these parameters offline. This often yields limited estimation accuracy due to high variance of RSSI measurements. To improve the estimation accuracy, the parameters are estimated together with the unknown node´s location in real time in this paper. To optimize the results, a new particle swarm optimization with log-barrier approach is proposed. Both simulation and experimental results show that the proposed scheme performs well as compared with some existing schemes.
  • Keywords
    particle swarm optimisation; radio transceivers; wireless sensor networks; RSSI measurements; anchor nodes; log-barrier constraint; nonlinear path loss model; particle swarm optimization; real-time estimation; received signal strength indicator; sensor node position; transceivers; wireless sensor network; Kalman filters; Particle swarm optimization; Position measurement; Real time systems; Wireless sensor networks; Extended Kalman filter (EKF); log-barrier method; particle swarm optimization (PSO); position measurement; wireless sensor network (WSN);
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/TIM.2011.2135030
  • Filename
    5755198