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Göteborgs universitets publikationer

Imaging of buried objects from experimental backscattering time dependent measurements using a globally convergent inverse algorithm

Författare och institution:
Nguyen Trung Thành (-); Larisa Beilina (Institutionen för matematiska vetenskaper, matematik, Chalmers/GU); Michael V. Klibanov (-); Michael A. Fiddy (-)
Publicerad i:
SIAM Journal of Imaging Sciences, 8 ( 1 ) s. 757-786
Serie:
Preprint - Department of Mathematical Sciences, Chalmers University of Technology and Göteborg University, ISSN 1652-9715; nr 2014:15
ISSN:
1936-4954
Antal sidor:
30 s.
Publikationstyp:
Artikel, refereegranskad vetenskaplig
Publiceringsår:
2015
Språk:
engelska
Fulltextlänk:
Fulltextlänk (lokalt arkiv):
Sammanfattning (abstract):
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.
Ämne (baseras på Högskoleverkets indelning av forskningsämnen):
NATURVETENSKAP ->
Matematik
Nyckelord:
buried object detection; coefficient identification problems; wave equation; globally convergent algorithm; experimental data; data preprocessing
Chalmers fundament:
Grundläggande vetenskaper
Postens nummer:
201567
Posten skapad:
2014-08-18 18:31
Posten ändrad:
2016-06-27 14:29

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