• Title of article

    A new method to simultaneously estimate the radius of a cylindrical object and the wave propagation velocity from GPR data

  • Author/Authors

    Ristic، نويسنده , , Aleksandar Vaso and Petrovacki، نويسنده , , Dusan and Govedarica، نويسنده , , Miro، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    11
  • From page
    1620
  • To page
    1630
  • Abstract
    We present a new method to simultaneously estimate cylindrical object radius (R) and electromagnetic (EM) wave propagation velocity (v) from ground penetrating radar (GPR) data. R estimation methods have been investigated since the middle of the previous decade, but studies have become more intensive and important over the last several years since they increase the utility of GPR data and enable new GPR applications. Since existing methods, according to the authorʹs best knowledge, are based on a priori known v, the proposed method has an advantage: it eliminates the measurement of v and its influence on R estimation quality. Estimating v accurately results in better soil characterisation. steps are used to simultaneously estimate v and R. First, using the extracted raw data, the coordinates of the hyperbola apex (x0, t0) are estimated. Second, the boundary speed (v0) is estimated, based on the previous results. In the final step, v is reduced from v0 to a predefined vmin. From the analysis of propagation velocity choice criterion, an optimal v is chosen, which is used to calculate a unique R. This proposed method is a nonlinear least squares fitting procedure. The method is implemented and verified, using data collected under real conditions, in a Matlab environment. arison of the proposed and existing methods shows that the new method is significantly more accurate and robust with regard to noise and the amount of raw data.
  • Keywords
    Propagation velocity , Least squares fitting , Radar scan , Hyperbolic reflection , Cylindrical object radius
  • Journal title
    Computers & Geosciences
  • Serial Year
    2009
  • Journal title
    Computers & Geosciences
  • Record number

    2287571