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Titolo:
Electromagnetic inverse scattering of two-dimensional perfectly conductingobjects by real-coded genetic algorithm
Autore:
Qing, A; Lee, CK; Jen, L;
Indirizzi:
Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore Nanyang Technol Univ Singapore Singapore 639798 gapore 639798, Singapore SW Jiaotong Univ, Inst Electromagnet Theory & Microwave Technol, Chengdu 610031, Peoples R China SW Jiaotong Univ Chengdu Peoples R China 610031 610031, Peoples R China
Titolo Testata:
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
fascicolo: 3, volume: 39, anno: 2001,
pagine: 665 - 676
SICI:
0196-2892(200103)39:3<665:EISOTP>2.0.ZU;2-Q
Fonte:
ISI
Lingua:
ENG
Soggetto:
BORN ITERATIVE METHOD; NONLINEAR ELASTIC INVERSION; MODIFIED GRADIENT-METHOD; HARMONIC ACOUSTIC-WAVES; ANNUAL SPECIAL SESSION; TIME-DOMAIN DATA; IMAGE-RECONSTRUCTION; NEURAL NETWORKS; DIELECTRIC CYLINDER; DIFFRACTION TOMOGRAPHY;
Keywords:
real-coded genetic algorithm; shape reconstruction; two-dimensional (2-D) perfectly conducting objects;
Tipo documento:
Review
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
154
Recensione:
Indirizzi per estratti:
Indirizzo: Qing, A Univ Gesamthsch Kassel, Dept Elect Engn, D-34109 Kassel, Germany Univ Gesamthsch Kassel Kassel Germany D-34109 09 Kassel, Germany
Citazione:
A. Qing et al., "Electromagnetic inverse scattering of two-dimensional perfectly conductingobjects by real-coded genetic algorithm", IEEE GEOSCI, 39(3), 2001, pp. 665-676

Abstract

Shape reconstruction of two-dimensional perfectly conducting objects usingnoisy measured scattering data is considered in this paper. The contour ofeach conducting object is denoted by a shape function in the local polar coordinate which is approximated by a trigonometric series. A point-matchingmethod is used to solve the scattering problem. The main idea of the inversion algorithm is to cast the inverse problem into a restrained minimization problem and to solve it by the real-coded genetic algorithm (RGA). The performance of this algorithm is demonstrated by numerically reconstructing arbitrarily shaped objects and by a detailed comparison with both the standard genetic algorithm (SGA) and the Newton-Kantorovitch method.

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Documento generato il 22/01/20 alle ore 18:50:33