DocumentCode
1875269
Title
Microwave Imaging Based on the AWE and HPSO Incorporated with the Information Obtained from Born Approximation
Author
Huang Guo-rong ; Zhong Wei-jun ; Liu Hua-wei
Author_Institution
Air Force Eng. Univ., Xi´an, China
fYear
2010
fDate
10-12 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
A novel approach for microwave imaging of the dielectric objects in free space using hybrid particle swarm optimization (HPSO) is presented in this paper. A scattering model based on the method of moment and the asymptotic waveform evaluation (AWE) is used to solve the scattering problem in this paper. The error between measured field and computed field is considered as the object function. The inverse scattering problem is transferred into an optimization problem by minimizing the object function, which is solved by hybrid particle swarm optimization. Comparisons of the Genetic Algorithms (GA) and hybrid particle swarm optimization are carried out. The results show that hybrid particle swarm optimization has the excellent performance imaging precision and robust anti-jamming. Another important advantage is that there is no necessary to utilize the regularization term which is essential to obtain the stabilization in application of typical direct optimization routine.
Keywords
electromagnetic wave scattering; genetic algorithms; inverse problems; method of moments; microwave imaging; particle swarm optimisation; Born approximation; anti-jamming; asymptotic waveform evaluation; dielectric objects; direct optimization routine; genetic algorithms; hybrid particle swarm optimization; inverse scattering problem; method of moment; microwave imaging; object function; regularization term; scattering model; Image reconstruction; Microwave imaging; Microwave theory and techniques; Optimization; Particle swarm optimization; Scattering;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5391-7
Electronic_ISBN
978-1-4244-5392-4
Type
conf
DOI
10.1109/CISE.2010.5676968
Filename
5676968
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