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APPLICATION OF MDL CRITERION FOR MICROWAVE IMAGING BY MUSIC ALGORITHM

By M. Pouramadi, M. Nakhkash, and A. A. Tadion

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Abstract:
Multiple signal classification (MUSIC) algorithm has been applied to localize small scatterers for super-resolution imaging. A problem associated with this application is the estimation of the number of scatterers in presence of noise and multiple scattering between targets. In this paper, we show that the mathematical model behind the scattering from the small objects is well compatible with the minimum description length (MDL) model. This leads us to use the MDL so as to estimate the number of scatterers before application of the MUSIC algorithm. As the MDL assumes the sources are independent, the nearby wave sources are grouped together to improve the independency criterion. The application of MDL to synthetic and experimental data verifies accurate estimation of the target number with low complexity, even if the data embodies significant noise and multiple scattering.

Citation:
M. Pouramadi, M. Nakhkash, and A. A. Tadion, "Application of Mdl Criterion for Microwave Imaging by MUSIC Algorithm," Progress In Electromagnetics Research B, Vol. 40, 261-278, 2012.
doi:10.2528/PIERB12031001

References:
1. Massa, A., G. Franceschini, M. Donelli, and R. Azaro, Inversion of phaseless total field data using a two step strategy based on the iterative multi scaling approach , IEEE Trans. on Geoscience and Remote Sensing, Vol. 44, No. 12, 3527-3539, 2006.

2. Donelli, M., I. J. Craddock, D. Gibbins, and M. Sarafianou, "A three-dimensional time domain microwave imaging method for breast cancer detection based on an evolutionary algorithm," Progress In Electromagnetics Research M, Vol. 18, 179-195, 2011.

3. Takenaka, T., H. Jia, and T. Tanaka, "Microwave imaging of electrical property distributions by a forward-backward time-stepping method," Journal of Electromagnetic Waves and Applications, Vol. 14, No. 12, 1609-1626, 2000.
doi:10.1163/156939300X00383

4. Massa, A., D. Franceschini, M. Donelli, and P. Rocca, "Three dimensional microwave imaging problems solved through an efficient multi scaling particle swarm optimization," IEEE Trans. on Geoscience and Remote Sensing, Vol. 47, No. 5, 1467-1481, 2009.
doi:10.1109/TGRS.2008.2005529

5. Weedon, W. H., W. C. Chew, and P. E. Mayes, "A step-frequency radar imaging system for microwave nondestructive evaluation," Progress In Electromagnetics Research, Vol. 28, 121-146, 2000.
doi:10.2528/PIER99062501

6. Liu, D. H., J. Krolik, and L. Carin, "Electromagnetic target detection in uncertain media: Time-reversal and minimum variance algorithms ," IEEE Trans. on Geoscience and Remote Sensing, Vol. 45, 934-944, 2007.
doi:10.1109/TGRS.2006.890411

7. Prada, C., S. Mannevile, D. Spoliansky, and M. Fink, "Decomposition of the time reversal operator: Detection and selective focusing on two scatterers," J. Acoust. Soc. Amer., Vol. 99, 2067-2076, 1996.
doi:10.1121/1.415393

8. Chambers, D. H. and J. G. Berryman, "Analysis of the time-reversal operator for a small spherical scatterer in an electromagnetic field," IEEE Trans. Antennas Propag., Vol. 52, 1729-1738, 2004.
doi:10.1109/TAP.2004.831323

9. Zhu, X., Z. Zhao, W. Yang, Y. Zhang, Z.-P. Nie, and Q. H. Liu, "Iterative time-reversal mirror method for imaging the buried object beneath rough ground surface," Progress In Electromagnetics Research, Vol. 117, 19-33, 2011.

10. Marengo, E. A., F. K. Gruber, and F. Simonetti, "Time-reversal MUSIC imaging of extended targets," IEEE Trans. Image Proc., Vol. 16, 1967-1984, 2007.
doi:10.1109/TIP.2007.899193

11. Zhang, W., A. Hoorfar, and L. Li, "Through-the-wall target localization with time reversal music method," Progress In Electromagnetics Research, Vol. 106, 75-89, 2010.
doi:10.2528/PIER10052408

12. Lehman, S. K. and A. J. Devaney, "Transmission mode time-reversal super resolution imaging," J. Acoust. Soc. Amer., Vol. 113, 2742-2752, 2003.
doi:10.1121/1.1566975

13. Lev-Ari, H. and A. J. Devaney, "The time reversal techniques reinterpreted: Subspace-based signal processing for multistatic target location," IEEE Sensor Array Multichannel Signal Proc., Workshop, 509-513, 2000.

14. Yavuz, M. E. and F. L. Teixeira, "Full time-domain DORT for ultrawideband fields in dispersive, random inhomogeneous media," IEEE Trans. Antennas Propag., Vol. 54, 2305-2315, 2006.
doi:10.1109/TAP.2006.879196

15. Zhao, H., "Analysis of the response matrix for an extended target," SIAM J. Appl. Math., Vol. 64, 725-745, 2004.
doi:10.1137/S0036139902415282

16. Yavuz, M. E. and F. L. Teixeira, "On the sensitivity of time-reversal imaging techniques to model perturbations," IEEE Trans. Antennas Propag., Vol. 56, 834-843, 2008.
doi:10.1109/TAP.2008.916933

17. Davy, F., J.-G. Minonzio, J. de Rosny, C. Prada, and M. Fink, "In°uence of noise on subwavelength imaging of two close scatterers using time reversal method: Theory and experiments," Progress In Electromagnetics Research, Vol. 98, 333-358, 2009.
doi:10.2528/PIER09071004

18. Anderson, T. W., "Asymptotic theory for principal component analysis," Ann. J. Math. Stat., Vol. 34, 122-148, 1963.
doi:10.1214/aoms/1177704248

19. Akaike, H., "A new look at the statistical model identification," IEEE Trans. Automat. Contr., Vol. 19, No. 6, 716-723, 1974.
doi:10.1109/TAC.1974.1100705

20. Rissanen, J., "Modeling by shortest data description," Automatira, Vol. 14, 465-471, 1978.
doi:10.1016/0005-1098(78)90005-5

21. Hannan, E. J., "The determination of the order of an autoregression," J. Roy. Srar. Soc. Bvol., Vol. 41, No. 2, 190-195, 1979.

22. Wax, W. and T. Kailath, "Detection of signals by information theoretic criteria," IEEE Trans. on Acoustic, Speech, and Signal Proc., Vol. 33, 387-392, 1985.
doi:10.1109/TASSP.1985.1164557

23. Haddadi, F., "Statistical performance analysis of mdl source enumeration in array processing," IEEE Trans. on Signal Proc., Vol. 58, 452-457, 2010.
doi:10.1109/TSP.2009.2028207

24. Devaney, A. J., Super-resolution processing of multi-static data using time reversal and MUSIC, Northeastern University Report, available at http://www.ece.neu.edu/faculty/devaney/ajd/preprints.htm.

25. Marengo, E. A. and F. K. Gruber, "Subspace-based localization and inverse scattering of multiply scattering point targets," EURASIP Journal on Advances in Signal Processing, 1-16, 2007.

26. Fishler, E. and H. V. Poor, "Estimation of the number of sources in unbalanced array via information theoretic criteria," IEEE Trans. on Signal Proc., Vol. 53, 3543-3553, 2005.
doi:10.1109/TSP.2005.853099

27. Fishler, E., M. Grossmann, and H. Messer, "Detection of signals by information theoretic criteria: General asymptotic performance analysis," IEEE Trans. on Signal Proc., Vol. 50, 1027-1036, 2002.
doi:10.1109/78.995060

28. Belkebir, K. and M. Saillard, "Special section: Testing inversion algorithms against experimental data," Inverse Problems, Vol. 17, 1565-1571, 2001.
doi:10.1088/0266-5611/17/6/301


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