• DocumentCode
    2980925
  • Title

    RSSI localization algorithm based on RBF neural network

  • Author

    Tian, Jiannan ; Xu, Zhan

  • Author_Institution
    Res. Inst. of Electron. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2012
  • fDate
    22-24 June 2012
  • Firstpage
    321
  • Lastpage
    324
  • Abstract
    This paper proposes a algorithm method of RBF neural network based on RSSI localization algorithm. It solves the question which through traditional filter algorithm, redundancy algorithm can not solve base on effect of multi-route propagation, and the complexity of signal attenuation environment. Simulation results demonstrate the validity of the algorithm, it can mitigate the effect of multi-route propagation, and localization precision can reach one meter or higher. On the side, this algorithm have higher convergence speed, it fits in embedded application. It can be designed as self-study and closed loop neural network in future.
  • Keywords
    Global Positioning System; filtering theory; radial basis function networks; telecommunication computing; RBF neural network; RSSI localization algorithm; closed loop neural network; convergence speed; embedded application; filter algorithm; multiroute propagation; receive signal strength indication; redundancy algorithm; signal attenuation environment; wireless positioning technology; Flowcharts; Artificial intelligence; Localization Algorithm; NLOS; RBF Neural Network; The Internet of things;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-2007-8
  • Type

    conf

  • DOI
    10.1109/ICSESS.2012.6269470
  • Filename
    6269470