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- Kuzhuget, A. V., et al.
(author)
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Quantitative image recovery from measured blind backscattered data using a globally convergent inverse method
- 2013
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In: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 51:5, s. 2937 - 2948
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Journal article (peer-reviewed)abstract
- The goal of this paper is to introduce the application of a globally convergent inverse scattering algorithm to estimate dielectric constants of targets using time-resolved backscattering data collected by a U.S. Army Research Laboratory forward-looking radar. The processing of the data was conducted blind, i.e., without any prior knowledge of the targets. The problem is solved by formulating the scattering problem as a coefficient inverse problem for a hyperbolic partial differential equation. The main new feature of this algorithm is its rigorously established global convergence property. Calculated values of dielectric constants are in a good agreement with material properties, which were revealed a posteriori.
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- Thành, Nguyen Trung, et al.
(author)
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Imaging of buried objects from experimental backscattering time dependent measurements using a globally convergent inverse algorithm
- 2015
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In: SIAM Journal on Imaging Sciences. - : Society for Industrial & Applied Mathematics (SIAM). - 1936-4954. ; 8:1, s. 757-786
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Journal article (peer-reviewed)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.
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