Optimization of inverse problems involving surface reconstruction: least squares application
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Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This article addresses the least-squares method, which is vital in inverse scattering problems involving the reconstruction of inaccessible rough surface profiles from the measured scattered field data. The unknown surface profile is retrieved by a regularized recursive Newton algorithm which is regularized by the Tikhonov method. The importance of the least-squares application reveals at this point, where the unknown surface profile is expressed as a linear combination of some appropriate basis functions. Thus, the problem of obtaining the unknown rough surface is reduced to finding the unknown coefficients of these functions. As an optimization problem, the choice of appropriate basis functions, as well as the number of their expansions for rough surface imaging problems are essential for the iterative solutions. The validation limits and the performances of different basis functions are presented via several numerical examples.
Açıklama
Anahtar Kelimeler
Electric fields, Functions, Iterative methods, Least squares approximations, Surface measurement, Surface reconstruction, Surface scattering, Base function, Inverse scattering problems, Least square, Least-squares- methods, Optimisations, Rough surfaces, Scattered field data, Surface profiles, Surfaces reconstruction, Unknown surface, Inverse problems, Electromagnetic scattering, Oceans and seas, Physical optics, Integral-equation, Scattering
Kaynak
2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Sefer, A. (2022). Optimization of inverse problems involving surface reconstruction: least squares application. Paper presented at the 2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting, AT-AP-RASC 2022, 1-4. doi:10.23919/AT-AP-RASC54737.2022.9814221
