Title :
Analyzing electromagnetic scattering using characteristic basis function method with compressed sensing
Author :
Quan-Quan Wang ; Tao Jin ; Hong-Bo Zhu ; Ru-Shan Chen
Author_Institution :
Dept. of Commun. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Abstract :
In this paper, the efficient analysis of electromagnetic scattering from objects is performed utilizing the characteristic basis function method (CBFM) with the compressed sensing (CS) technique. CBFM generates sets of high-level basis functions, i.e. the characteristic basis function (CBF), defined over macro domains of the object under discussion, to significantly reduce the matrix size and storage and make the reduced linear system easily manageable and solvable. In the conventional fulfillment, to generate the CBF, a series of matrix equations need to be solved repeatedly with various excitations of multiple incident angles and different polarizations. With the help of CS, much fewer excitations are necessary to solve the matrix equations, and one can obtain the measurements of the induced currents accordingly. Finally, the orthogonal matching pursuit (OMP) method is used to reconstruct the real induced currents and from which the CBF is generated. Numerical examples are included to demonstrate the performance of the proposed method.
Keywords :
compressed sensing; electromagnetic wave scattering; matrix algebra; CBFM; characteristic basis function method; compressed sensing technique; electromagnetic scattering; high-level basis functions; matrix equations; matrix size; orthogonal matching pursuit method; reduced linear system; Antennas; Compressed sensing; Educational institutions; Electromagnetic scattering; Equations; Integral equations; Matching pursuit algorithms; characteristic basis function method; compressed sensing; electromagnetic scattering;
Conference_Titel :
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-2763-0
DOI :
10.1109/CISP.2013.6743938