DocumentCode :
247833
Title :
Fast computing of large 3D dielectric forest scattering problems using the Characteristic Basis Function Method with the Adaptative Cross Approximation algorithm
Author :
Fenni, Ines ; Roussel, Helene ; Darces, Muriel ; Mittra, Raj
Author_Institution :
L2E, UPMC Univ. Paris 06, Paris, France
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
2002
Lastpage :
2003
Abstract :
This paper presents the hybridation of the Characteristic Basis Function Method with the Adaptative Cross Approximation algorithm while generating the reduced linear equation system. The proposed method is applied to 3D scattering model in the context of forest remote sensing. It enables us to realize a significant improvement of the performances of the CBFM both in terms of memory use and CPU time while maintaining a good level of accuracy compared to the CBFM solution.
Keywords :
approximation theory; electromagnetic wave scattering; remote sensing; 3D scattering model; CBFM solution; CPU time; adaptative cross approximation algorithm; characteristic basis function method; forest remote sensing; large 3D dielectric forest scattering problems; reduced linear equation system; Algorithm design and analysis; Approximation algorithms; Approximation methods; Mathematical model; Method of moments; Scattering; Vegetation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Antennas and Propagation Society International Symposium (APSURSI), 2014 IEEE
Conference_Location :
Memphis, TN
ISSN :
1522-3965
Print_ISBN :
978-1-4799-3538-3
Type :
conf
DOI :
10.1109/APS.2014.6905328
Filename :
6905328
Link To Document :
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