• DocumentCode
    1605111
  • Title

    Detection and classification of landmines using AR modeling of GPR data

  • Author

    Deiana, Daniela ; Anitori, Laura

  • Author_Institution
    TNO Defence, Security & Safety, The Hague, Netherlands
  • fYear
    2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper we present some results on detection and classification of low metal content anti personnel (AP) landmines using a modified version of the Auto Regressive (AR) modeling algorithm presented in. A statistical distance is computed between the AR coefficients of the measured GPR time signal and the AR coefficients of a reference database (containing the AR models of the mines of interest) and a detection is declared if this distance is below a given threshold.
  • Keywords
    autoregressive processes; ground penetrating radar; landmine detection; radar detection; AR coefficients; GPR data AR modeling; GPR time signal; autoregressive modeling algorithm; landmine classification; low metal content antipersonnel landmine detection; reference database; Aluminum; Databases; Electromagnetic measurements; Electromagnetic modeling; Finite difference methods; Ground penetrating radar; Landmine detection; Radar antennas; Soil; Time domain analysis; AR Modeling; GPR; Landmines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ground Penetrating Radar (GPR), 2010 13th International Conference on
  • Conference_Location
    Lecce
  • Print_ISBN
    978-1-4244-4604-9
  • Electronic_ISBN
    978-1-4244-4605-6
  • Type

    conf

  • DOI
    10.1109/ICGPR.2010.5550141
  • Filename
    5550141