• DocumentCode
    2833316
  • Title

    Air Target Classification in Two Dimensional Feature Space

  • Author

    Golmohammad, Hassan ; Bolandi, Hossein ; Saberi, Farhad Fani

  • Author_Institution
    Iran Univ. of Sci. & Technol., Tehran
  • fYear
    2006
  • fDate
    15-17 Dec. 2006
  • Firstpage
    518
  • Lastpage
    522
  • Abstract
    Results of two classifier is combined to make more reliable decision about the type of airplanes. Two classifiers are maximum acceleration classifier, which is implemented as an IMM filter, and maximum speed classifier which is a classical Bayesian classifier. Since TBM in data fusion applications is a cautious algorithm, it is adopted for this purpose. Finally, Monte Carlo simulation was carried out to show the efficiency of proposed approach.
  • Keywords
    Bayes methods; Monte Carlo methods; aerospace computing; filtering theory; sensor fusion; signal classification; target tracking; Bayesian classifier; IMM filter; Monte Carlo simulation; air target classification; airplane classification; data fusion; maximum acceleration classifier; maximum speed classifier; Acceleration; Data mining; Feature extraction; Intelligent sensors; Sensor fusion; Sensor phenomena and characterization; Sensor systems and applications; Space technology; Surveillance; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
  • Conference_Location
    Mumbai
  • Print_ISBN
    1-4244-0726-5
  • Electronic_ISBN
    1-4244-0726-5
  • Type

    conf

  • DOI
    10.1109/ICIT.2006.372312
  • Filename
    4237634