Mar. 31, 1999 to Apr. 3, 1999
Haihua Feng , Boston University
David A. Castanon , Boston University
W. Clem Karl , Boston University
This paper develops new approaches for imaging weak-contrast buried objects using data from a ground penetrating radar array. An approximate physical model relating the collected data to the underground objects is developed. This model uses ray optics to represent the air/soil interface, and a Born approximation to model the weak contrast back-scattering from buried objects. In order to address both modeling errors and ill-posedness, the proposed image reconstruction algorithms use regularization based on a total variation norm with orientation preference. The algorithms are tested on data generated by nonlinear finite difference time domain electromagnetic simulations.
regularization, GPR, Born approximation, FDTD, underground imaging
Haihua Feng, David A. Castanon, W. Clem Karl, "Underground Imaging Based on Edge-Preserving Regularization", ICIIS, 1999, Information, Intelligence, and Systems, International Conference on, Information, Intelligence, and Systems, International Conference on 1999, pp. 460, doi:10.1109/ICIIS.1999.810316