Detection, reconstruction, and characterization algorithms from noisy data in multistatic wave imaging
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Ammari-2015-Detection.pdf
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465.64 KB
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Author(s)
Ammari, Habib
Garnier, Josselin
Jugnon, Vincent
Date Issued
October 2014
Journal
Discrete and Continuous Dynamical Systems - Series S
Publisher
American Institute of Mathematical Sciences (AIMS)
Citation
Ammari, Habib, Josselin Garnier, and Vincent Jugnon. “Detection, Reconstruction, and Characterization Algorithms from Noisy Data in Multistatic Wave Imaging.” DCDS-S 8, no. 3 (October 2014): 389–417. doi:10.3934/dcdss.2015.8.389. © American Institute of Mathematical Sciences
Version
Final published version
Abstract
The detection, localization, and characterization of a collection of targets embedded in a medium is an important problem in multistatic wave imaging. The responses between each pair of source and receiver are collected and assembled in the form of a response matrix, known as the multi-static response matrix. When the data are corrupted by measurement or instrument noise, the structure of the response matrix is studied by using random matrix theory. It is shown how the targets can be efficiently detected, localized and characterized. Both the case of a collection of point reflectors in which the singular vectors have all the same form and the case of small-volume electromagnetic inclusions in which the singular vectors may have different forms depending on their magnetic or dielectric type are addressed.
MIT Department
Massachusetts Institute of Technology. Department of Mathematics
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.3934/dcdss.2015.8.389
