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2008-04-24
On the Target Classification through Wavelet-Compressed Scattered Ultrawide-Band Electric Field Data and ROC Analysis
By
Progress In Electromagnetics Research, Vol. 82, 419-431, 2008
Abstract
This paper's aim is to classify cylindrical targets from their ultrawide-band radar returns. To calculate the radar returns, image technique formulation is used to obtain the Electric Field Integral Equations (EFIEs). Then, the EFIEs are solved numerically by Method of Moment (MoM). Because of wide frequency range of the ultrawide-band radar signal, the database to be used for target classification becomes very large. To deal with this problem and to provide robustness, wavelet transform is utilized. Application of wavelet transform significantly reduces the size of the database. The coefficients obtained by wavelet transform are used as the inputs of the artificial neural networks (ANNs). Then, the actual performances of the networks are investigated by Receiver Operating Characteristic (ROC) analysis.
Citation
Senem Makal, Ahmet Kizilay, and Lutfiye Durak, "On the Target Classification through Wavelet-Compressed Scattered Ultrawide-Band Electric Field Data and ROC Analysis," Progress In Electromagnetics Research, Vol. 82, 419-431, 2008.
doi:10.2528/PIER08040903
References

1. Yang, Y., "MIMO radar waveform design based on mutual information and minimum mean-square error estimation," IEEE Transactions on Aerospace and Electronic Systems, Vol. 43, No. 1, 330-343, 2007.
doi:10.1109/TAES.2007.357137

2. Park, S. E., "Unsupervised classification of scattering mechanisms in polarimetric SAR data using fuzzy logic in entropy and alpha plane," IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 8, 2652-2664, 2007.
doi:10.1109/TGRS.2007.897691

3. Turhan, G., "Real time electromagnetic target classification using a novel feature extraction technique with PCA-based fusion," IEEE Transaction on Antennas and Propagation, Vol. 53, No. 2, 766-776, 2005.
doi:10.1109/TAP.2004.841326

4. Chen, X., D. Liang, and K. Huang, "Microwave imaging 3-d buried objects using parallel genetic algorithm combined with FDTD technique," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 13, 1761-1774, 2006.
doi:10.1163/156939306779292264

5. Xue, W. and X.-W. Sun, "Target detection of vehicle volume detecting radar based on Wigner-Hough transform," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 11, 1513-1523, 2007.

6. Li, Y.-L., J.-Y. Huang, and M.-J. Wang, "Investigation of electromagnetic interaction between a spherical target and a conducting plane," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 12, 1703-1715, 2007.

7. Alivizatos, E. G., M. N. Petsios, and N. K. Uzunoglu, "Towards a range-doppler UHF multistatic radar for the detection of noncooperative targets with low RCS," Journal of Electromagnetic Waves and Applications, Vol. 19, No. 15, 2015-2031, 2005.
doi:10.1163/156939305775570512

8. Lee, K.-C. and J.-S. Ou, "Radar target recognition by using linear discriminant algorithm on angular-diversity RCS," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 14, 2033-2048, 2007.
doi:10.1163/156939307783152902

9. Zainud-Deen, S. H., M. E. Badr, E. El-Deen, K. H. Awadalla, and H. A. Sharshar, "Microstrip antenna with corrugated ground plane surface as a sensor for landmines detection," Progress In Electromagnetics Research B, Vol. 2, 259-278, 2008.
doi:10.2528/PIERB07112702

10. Ozdemir, C., S. Demirci, and E. Yigit, "Practical algorithms to focus B-scan GPR images: theory and application to real data," Progress In Electromagnetics Research B, Vol. 6, 109-122, 2008.

11. Azimi-Sadjadi, M. R., D. Yao, Q. Huang, and G. J. Dobeck, "Underwater target classification using wavelet packets and neural networks," IEEE Trans. on Neural Networks, Vol. 11, No. 3, 784-794, 2000.
doi:10.1109/72.846748

12. Ak, U., T. Gnel, and I. Erer, "A wavelet-based radial-basis function neural networkapproac h to the conducting cylinders," Microwave and Optical Technology Letters, Vol. 41, No. 6, 506-511, 2004.
doi:10.1002/mop.20186

13. Hassani, H. R. and M. Jahanbakht, "Method of moment analysis of finite phased array of aperture coupled circular microstrip patch antennas," Progress In Electromagnetics Research B, Vol. 4, 197-210, 2008.

14. Kizilay, A. and S. Makal, "A neural network solution for identification and classification of cylindrical targets above perfectly conducting flat surfaces," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 14, 2147-2156, 2007.
doi:10.1163/156939307783152759

15. Kizilay, A., A perturbation method for transient multipath analysis of electromagnetic scattering from targets above periodic surfaces, Ph.D. dissertation, Michigan State University, 2000.

16. Strang, G. and T. Nyugen, Wavelets and Filterbanks, Wellesley-Cambridge Press, Massachusetts, 1997.

17. Arivazhagan, S., W. S. L. Jebarani, and G. Kumaran, "Performance comparison of discrete wavelet transform and dual tree discrete wavelet transform for automatic airborne target detection," International Conference on Computational Intelligence and Multimedia Applications, 495-500, 2007.

18. Zhang, R., G. McAllister, B. Scotney, S. McClean, and G. Houston, "Combining wavelet analysis and Bayesian networks for the classification of auditory brainstem response," IEEE Transactions on Information Technology in Biomedicine, Vol. 10, No. 3, 458-467, 2006.
doi:10.1109/TITB.2005.863865

19. Bors, A. G. and M. Gabbouj, "Neural networks and radial basis function neural networkfor pattern classification," Digital Signal Processing: A Review Journal, Vol. 4, No. 3, 173-188, 1994.
doi:10.1006/dspr.1994.1016

20. Zainud-Deen, S. H., H. A. Malhat, K. H. Awadalla, and E. S. El-Hadad, "Direction of arrival and state of polarization estimation using radial basis function neural network(RBFNN)," Progress In Electromagnetics Research B, Vol. 2, 137-150, 2008.
doi:10.2528/PIERB07111801

21. Mohamed, M. D. A., E. A. Soliman, and M. A. El-Gamal, "Optimization and characterization of electromagnetically coupled patch antennas using RBF neural networks," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 8, 1101-1114, 2006.
doi:10.1163/156939306776930240

22. Park, J. and W. I. Sandberg, "Universal approximation using radial basis function networks," Neural Computation, Vol. 3, No. 2, 246-257, 1991.
doi:10.1162/neco.1991.3.2.246

23. Mohamed, M. D. A., E. A. Soliman, and M. A. El-Gamal, "Optimization and characterization of electromagnetically coupled patch antennas using RBF neural networks," Journal of Electromagnetic Wave and Applications, Vol. 20, No. 8, 1101-1114, 2006.
doi:10.1163/156939306776930240

24. Rutkowski, L., "Generalized regression neural networks in time-varying environment," IEEE Transactions on Neural Networks, Vol. 15, No. 3, 576-596, 2004.
doi:10.1109/TNN.2004.826127

25. Haykin, S., Neural Networks: A Comprehensive Foundation, Macmillan College Publishing, New York, 1994.

26. Guney, K., C. Yildiz, S. Kaya, and M. Turkmen, "Artificial neural networks for calculating the characteristic impedance of air-suspended trapezoidal and rectangular-shaped microshield lines," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 9, 1161-1174, 2006.
doi:10.1163/156939306777442917

27. Schalkoff, R. J., Artificial Neural Networks, McGraw-Hill Inc., Singapore, 1997.

28. Sboner, A., "Multiple classifier system for early melanoma diagnosis," AI in Medicine, Vol. 27, No. 1, 29-44, 2003.

29. Wang, S., C. I. Chang, S. C. Yang, G. C. Hsu, H. H. Hsu, P. C. Chung, S. M. Gua, and S. K. Lee, "3D ROC analysis for medical imaging diagnosis," IEEE International Conference of the Engineering in Medicine and Biology, 7545-7548, 2005.