• DocumentCode
    2736762
  • Title

    A neural network approach towards multiradar track fusion

  • Author

    Mohandes, M. ; Bogner, R.E. ; Bouzerdoum, A. ; Pope, K.J.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Adelaide Univ., SA, Australia
  • Volume
    3
  • fYear
    1996
  • fDate
    3-6 Jun 1996
  • Firstpage
    1616
  • Abstract
    The Jindalee operational over-the-horizon radar network has three radar stations which overlap in their coverage. Consequently, targets may be detected by more than one radar. Multiple tracks from one target present a large operator workload, especially at where regions overlap. This paper introduces a method to automate the track association process. Multilayer perceptron and statistical decision systems are used to classify tracks into associated and nonassociated pairs
  • Keywords
    multilayer perceptrons; radar computing; radar target recognition; radar tracking; sensor fusion; statistical analysis; target tracking; Australia; Jindalee operational over-the-horizon radar network; OTH radar; associated pairs; multilayer perceptron; multiradar track fusion; neural network approach; nonassociated pairs; statistical decision systems; Australia; Data mining; Earth; Frequency; Ionosphere; Neural networks; Radar detection; Radar signal processing; Radar tracking; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1996., IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-3210-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1996.549142
  • Filename
    549142