• DocumentCode
    2767720
  • Title

    Multisensor Data Fusion Using Neural Networks

  • Author

    Yadaiah, N. ; Singh, Lakshman ; Bapi, R.S. ; Rao, V. Srinivasa ; Deekshatulu, B.L. ; Negi, Atul

  • Author_Institution
    Jawaharlal Nehru Technol. Univ., Hyderabad
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    875
  • Lastpage
    881
  • Abstract
    This paper presents a Hebbian learning based linear single-layer neural network based measurement fusion of multisensor data. The performance of the proposed unsupervised neural network algorithm is compared with traditional fusion methods based on Kalman filtering such as measurement fusion and state vector fusion. The experiments have been carried out using multisensor data obtained from different radars. The results demonstrate the viability of the proposed algorithm.
  • Keywords
    Kalman filters; neural nets; sensor fusion; Kalman filtering; hebbian learning; linear single-layer neural network; measurement fusion; multisensor data fusion; radars; state vector fusion; unsupervised neural network algorithm; Assembly systems; Computer networks; Data engineering; Electric variables measurement; Hebbian theory; Intelligent sensors; Kalman filters; Neural networks; Radar detection; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246777
  • Filename
    1716188