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Journal article
Reduced Order Modeling Inversion of Monostatic Data in a Multi-scattering Environment
SIAM journal on imaging sciences, v 17(1), pp 334-350
01 Jan 2024
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Data-driven reduced order models (ROMs) have recently emerged as an efficient tool for the solution of inverse scattering problems with applications to seismic and sonar imaging. One requirement of this approach is that it uses the full square multiple-input/multiple-output (MIMO) matrix-valued transfer function as the data for multidimensional problems. The synthetic aperture radar(SAR), however, is limited to the single-input/single-output (SISO) measurements corresponding to the diagonal of the matrix transfer function. Here we present a ROM-based Lippmann--Schwinger approach overcoming this drawback. The ROMs are constructed to match the data for each source-receiver pair separately, and these are used to construct internal solutions for the corresponding source using only the data-driven Gramian. Efficiency of the proposed approach is demonstrated on2D and 2.5D (3D propagation and 2D reflectors) numerical examples. The new algorithm not only suppresses multiple echoes seen in the Born imaging but also takes advantage of their illumination of some back sides of the reflectors, improving the quality of their mapping.
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2 citations in Scopus
Details
- Title
- Reduced Order Modeling Inversion of Monostatic Data in a Multi-scattering Environment
- Creators
- Vladimir Druskin - Worcester Polytechnic InstituteShari Moskow - Drexel UniversityMikhail Zaslavsky - Southern Methodist University
- Publication Details
- SIAM journal on imaging sciences, v 17(1), pp 334-350
- Publisher
- Siam Publications
- Number of pages
- 17
- Grant note
- DMS-1929284; DMS-2110773; DMS-2008441 / NSF; National Science Foundation (NSF) Spring 2020 Reunion Event FA 955020-1-0079; FA9550-20-1-0079 / AFOSR; United States Department of Defense; Air Force Office of Scientific Research (AFOSR)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mathematics
- Web of Science ID
- WOS:001195370800014
- Scopus ID
- 2-s2.0-85199629084
- Other Identifier
- 991021867237304721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas