Detection, reconstruction, and characterization algorithms from noisy data in multistatic wave imaging
Author(s)
Ammari, Habib; Garnier, Josselin; Jugnon, Vincent
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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.
Date issued
2014-10Department
Massachusetts Institute of Technology. Department of MathematicsJournal
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
ISSN
1937-1632