Application of SVM and BCG-FFT Method for the Parameter Reconstruction of Composite Conducting-Dielectric Cylinder
Keywords:
Biconjugate Gradient Fast Fourier Transform (BCG-FFT), composite conductingdielectric cylinder, parameter reconstruction and Support Vector Machine (SVM)Abstract
In this paper, Support Vector Machine (SVM) technique is used to reconstruct the geometric and dielectric characteristics of composite conducting-dielectric cylinder. To this aim, the scattered electric fields at a number of observation points by composite conductingdielectric object under the different object parameters are calculated by stabilized Biconjugate Gradient Fast Fourier Transform method (BCG-FFT) and provide to SVM as input training samples, while the output of the SVM are the characteristics of the objects. In numerical results, the proposed technique is applied successfully to the reconstruction of the geometric and dielectric parameters of composite conducting-dielectric cylinder. The effectiveness of the SVM method is evaluated and also in comparison with the Neural Network (NN) based approaches.
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S. M. Rao, C. C. Cha, R. L. Cravey, and D. L. Wilkes, “Electromagnetic scattering from arbitrary shaped conducting bodies coated with lossy materials of arbitrary thickness,” IEEE Trans. Antennas Propag., vol. 39, no. 5, pp. 627-631, 1991.
T. K. Sarkar and E. Arvas, “An integral equation approach to the analysis of finite microstrip antennas: volume/surface formulation,” IEEE Trans. Antennas Propag., vol. 38, no. 3, pp. 305- 313, 1990.
C. C. Lu and W. C. Chew, “A coupled surfacevolume integral equation approach for the calculation of electromagnetic scattering from composite metallic and material targets,” IEEE Trans. Antennas Propag., vol. 48, no. 12, pp. 1866- 1868, 2000.
X. C. Nie, N. Yuan, L. W. Li, Y. B. Gan, and T. S. Yeo, “A fast volume-surface integral equation solver for scattering from composite conductingdielectric objects,” IEEE Trans. Antennas Propag., vol. 53, no. 2, pp. 818-823, 2005.
M. A. Carr, E. Topsakal, J. L. Volakis, and D. C. Ross, “Adaptive integral method applied to multilayer penetrable scatterers with junctions,” In IEEE Antennas Propag. Soc. Int. Sypm., pp. 856- 861, 2001
R. Mydur and K. A. Michalski, “A neural network approach to the electromagnetic imaging of elliptic conducting cylinders,” Microwave Opt. Technol. Lett., vol. 28, no. 5, pp. 303-306, 2001.
I. T. Rekanos, “On-line inverse scattering of conducting cylinders using radial basis-function neural networks,” Microwave Opt. Technol. Lett., vol. 28, no. 6, pp. 378-380, 2001.
E. Bermani, S. Caorsi, and M. Raffetto, “An inverse scattering approach based on a neural network technique for the detection of dielectric cylinders buried in a lossy half-space,” PIER, vol. 26, pp. 67-87, 2000.
E. Bermani, S. Caorsi, and M. Raffetto, “Microwave detection and dielectric characterization of cylindrical objects from amplitude-only data by means of neural networks,” IEEE Trans. Antennas Propag., vol. 50, no. 9, pp. 1309-1314, 2002.
E. Bermani, S. Caorsi, and M. Raffetto, “Geometric and dielectric characterization of buried cylinders by using simple time-domain electromagnetic data and neural networks,” Microwave Opt. Technol. Lett., vol. 24, no. 1, pp. 24-31, 2000.
E. Bermani, A. Boni, S. Caorsi, and A. Massa, “An innovation real-time technique for buried object detection,” IEEE Trans. Geosci. Remote Sens., vol. 41, no. 4, pp. 927-931, 2003.
Q. H. Zhang, B. X. Xiao, and G. Q. Zhu, “Inverse scattering by dielectric cylinder using support vector machine approach,” Microwave Opt. Technol. Lett., vol. 49, no. 2, pp. 372-375, 2007.
V. Vapnik, “Statistical learning theory,” New York: Wiley, 1998.
R. Coifman, V. Rokhlin, and S. Wandzura, “The fast multipole method for the wave equation: a pedestrian prescription,” IEEE Antennas Propag., vol. 35, pp. 7-12, 1993.
J. M. Song, C. C. Lu, and W. C. Chew, “Multilevel fast-multipole algorithm for electromagnetic scattering by large complex objects,” IEEE Trans. Antennas Propag., vol. 45, no. 10, pp. 1488-1493, 1997.
T. K. Sarkar, E. Arvas, and S. M. Rao, “Application of FFT and conjugate gradient method for the solution of electromagnetic radiation from electrically large and small conducting bodies,” IEEE Trans. Antennas and Propagate., vol. 34, no. 5, pp. 635-640, 1986.
E. Bleszynski, M. Bleszynski, and T. Jaroszewicz, “AIM: adaptive integral method for solving large scale electromagnetic scattering and radiate on problems,” Radio Sci., vol. 31, pp. 1225-1251, 1996.
X. M. Xu, Q. H. Liu, and Z. Q. Zhang, “The stabilized biconjugate fradient fast fourier transform method for electromagnetic scattering,” J. Appl. Computat. Electromagn., vol. 17, no. 1, pp. 97-103, 2002.
N. Cristianini and J. S. Taylor, “An introduction to support vector machine,” Cambridge Univ. Press, Cambridge, U.K., 2000.
J. Platt, “Fast training of support vector machine using sequential minimal optimization,” In: B. Scolkopf, C. Burges, and A. Smola (Eds.), “Advances in kernel methods-support vector learning,” MIT Press, Cambridge, MA, 1999.
L. Pasolli, C. Notarnicola, and L. Bruzzone, “Estimating soil moisture with the support vector regression technique,” IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 6, pp. 1080- 1084, 2011.
A. Z. Elsherbeni and A. A. Kishk, “Modeling of cylindrical objects by circular dielectric and conducting cylinders,” IEEE Trans. Antennas and Propag., vol. 40, no. 1, pp. 96-99, 1992.
