Imaging of buried objects from experimental backscattering time dependent measurements using a globally convergent inverse algorithm
Artikel i vetenskaplig tidskrift, 2015

We consider the problem of imaging of objects buried under the ground using experimental back-scattering time-dependent measurements generated by a single point source or one incident plane wave. In particular, we estimate dielectric constants of these objects using the globally convergent inverse algorithm of Beilina and Klibanov. Our algorithm is tested on experimental data collected using a microwave scattering facility at the University of North Carolina at Charlotte. There are two main challenges in working with this type of experimental data: (i) there is a huge misfit between these data and computationally simulated data, and (ii) the signals scattered from the targets may overlap with and be dominated by the reflection from the ground's surface. To overcome these two challenges, we propose new data preprocessing steps to make the experimental data look similar to the simulated data, as well as to remove the reflection from the ground's surface. Results of a total of 25 data sets of both nonblind and blind targets indicate good accuracy.

buried object detection

data preprocessing

coefficient identification problems

experimental data

globally convergent algorithm

wave equation


Nguyen Trung Thành

The University of North Carolina at Charlotte

Iowa State University

Larisa Beilina

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Matematik

Michael V. Klibanov

The University of North Carolina at Charlotte

Michael A. Fiddy

The University of North Carolina at Charlotte

SIAM Journal on Imaging Sciences

1936-4954 (ISSN)

Vol. 8 757-786




Grundläggande vetenskaper



Preprint - Department of Mathematical Sciences, Chalmers University of Technology and Göteborg University: 2014:15