DocumentCode :
1756531
Title :
Nonlinear Inversion of Microwave Scattering Data for Snow-Covered Sea-Ice Dielectric Profile Reconstruction
Author :
Firoozy, Nariman ; Mojabi, Puyan ; Barber, David G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Manitoba, Winnipeg, MB, Canada
Volume :
12
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
209
Lastpage :
213
Abstract :
A nonlinear electromagnetic inverse scattering algorithm is presented to reconstruct snow-covered sea-ice dielectric profiles using multiple-frequency multipolarimetric normalized radar cross-sectional data. This inversion algorithm utilizes a global optimization technique in conjunction with the boundary-perturbation-theory electromagnetic forward solver to retrieve the complex permittivities, thickness values, and roughness parameters of the snow-covered sea-ice profiles of interest. The proposed algorithm is then tested against synthetically collected data in both bistatic and monostatic configurations. The achievable quantitative accuracy of the inversion results is reasonable as long as sufficient scattering data are given to the inversion algorithm.
Keywords :
inverse problems; iterative methods; oceanographic techniques; permittivity; perturbation theory; sea ice; snow; bistatic configurations; boundary perturbation theory; complex permittivities; electromagnetic forward solver; global optimization technique; inversion algorithm; microwave scattering data; monostatic configurations; multiple-frequency multipolarimetric normalized radar cross-sectional data; nonlinear electromagnetic inverse scattering algorithm; nonlinear inversion; roughness parameters; snow-covered sea-ice dielectric profile reconstruction; thickness values; Dielectrics; Image reconstruction; Permittivity; Scattering; Sea ice; Snow; Arctic dielectric profile; boundary perturbation theory (BPT); differential evolution; electromagnetic inverse scattering; global optimization; snow-covered young ice (YI);
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2014.2332534
Filename :
6853312
Link To Document :
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