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

Authors:
Aleksandar Vaso Ristic;Dusan Petrovacki;Miro Govedarica
Affiliations:
Faculty of technical sciences, University of Novi Sad, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia;Faculty of technical sciences, University of Novi Sad, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia;Faculty of technical sciences, University of Novi Sad, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia
Venue:
Computers & Geosciences
Year:
2009

Citing 4
Cited 3

On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds

Mathematical Programming: Series A and B
Direct Least Square Fitting of Ellipses

IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Bias of Conic Fitting and Renormalization

IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Least Squares Fitting of Ellipses

ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270

Ground penetrating radar image preprocessing for embedded object in media

AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Ground penetrating radar slice reconstruction for embedded object in media with target follow

WSEAS Transactions on Computers
Using pattern recognition to automatically localize reflection hyperbolas in data from ground penetrating radar

Computers & Geosciences

Quantified Score

Hi-index	0.00

Visualization

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 author's 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. Three steps are used to simultaneously estimate v and R. First, using the extracted raw data, the coordinates of the hyperbola apex (x"0, t"0) are estimated. Second, the boundary speed (v"0) is estimated, based on the previous results. In the final step, v is reduced from v"0 to a predefined v"m"i"n. 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. A comparison 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.