PIER M
 
Progress In Electromagnetics Research M
ISSN: 1937-8726
Home | Search | Notification | Authors | Submission | PIERS Home | EM Academy
Home > Vol. 42 > pp. 169-177

THROUGH WALL DETECTION WITH RELEVANCE VECTOR MACHINE

By F.-F. Wang, Y.-R. Zhang, H.-M. Zhang, L. Hai, and G. Chen

Full Article PDF (160 KB)

Abstract:
In this paper, through-wall detection problem using a data-driven model is addressed. The original problem is cast into a regression one and successively solved by means of the relevance vector machine (RVM). Multiple scattering is included in the nonlinear relationship between the feature vector extracted from the backscattered field and the position of the target obtained through a training phase using RVM; hence the nonlinearity inherent in the problem is considered. Besides, the presence of the wall is also contained in this relationship. The predictions obtained by RVM are probabilistic which capture uncertainty, and we can define error-bars for the predicted results. Therefore, the ill-posed nature of the problem is accounted for naturally, rather than using other regularization schemes. To access the effectiveness, accuracy and robustness of the proposed approach, numerical results related to a two-dimensional geometry are presented. This method is demonstrated efficient qualitatively and quantitatively.

Citation:
F.-F. Wang, Y.-R. Zhang, H.-M. Zhang, L. Hai, and G. Chen, "Through Wall Detection with Relevance Vector Machine," Progress In Electromagnetics Research M, Vol. 42, 169-177, 2015.
doi:10.2528/PIERM15050502

References:
1. Song, L. P., C. Yu, and Q. H. Liu, "Through-wall imaging (TWI) by radar: 2-D tomographic results and analyses," IEEE Trans. Geosci. Remot. Sens., Vol. 43, No. 12, 2793-2798, 2005.
doi:10.1109/TGRS.2005.857914

2. Baranoski, E. J., "Through-wall imaging: Historical perspective and future directions," J. Frank. Inst., Vol. 345, No. 6, 556-569, 2008.
doi:10.1016/j.jfranklin.2008.01.005

3. Ferris, D. D. and N. C. Currie, "Survey of current technologies for through-the-wall surveillance (TWS)," Proc. SPIE, Vol. 3577, 62-72, 1999.
doi:10.1117/12.336988

4. Soldovieri, F., F. Ahmad, and R. Solimene, "Validation of microwave tomographic inverse scattering approach via through-the-wall experiments in semicontrolled conditions," IEEE Geosc. Rem. Sens. Lett., Vol. 8, No. 1, 123-127, 2011.
doi:10.1109/LGRS.2010.2051014

5. Ahmad, F., M. G. Amin, and S. A. Kassam, "Synthetic aperture beamformer for imaging through a dielectric wall," IEEE Trans. Aerosp. Electron. Syst., Vol. 41, No. 1, 271-283, 2005.
doi:10.1109/TAES.2005.1413761

6. Ahmad, F., M. G. Amin, and G. Mandapati, "Autofocusing of through-the-wall radar imagery under unknown wall characteristics," IEEE Trans. on Image Proc., Vol. 16, No. 7, 1785-1795, 2007.
doi:10.1109/TIP.2007.899030

7. Dehmollaian, M. and K. Sarabandi, "Refocusing through building walls using synthetic aperture radar," IEEE Trans. Geosci. Remot. Sens., Vol. 46, No. 6, 1589-1599, 2008.
doi:10.1109/TGRS.2008.916212

8. Soldovieri, F. and R. Solimene, "Through-wall imaging via a linear inverse scattering algorithm," IEEE Geosc. Rem. Sens. Lett., Vol. 4, No. 4, 513-517, 2007.
doi:10.1109/LGRS.2007.900735

9. Soldovieri, F., R. Solimene, and G. Prisco, "A multiarray tomographic approach for through-wall imaging," IEEE Trans. Geosci. Remot. Sens., Vol. 46, No. 4, 1192-1199, 2008.
doi:10.1109/TGRS.2008.915754

10. Chew, W. C. and Y. M. Wang, "Reconstruction of 2-dimensional permittivity distribution using the distorted born Iterative method," IEEE Trans. Med. Imag., Vol. 9, No. 2, 218-225, 1990.
doi:10.1109/42.56334

11. Cui, T. J., W. C. Chew, A. A. Aydiner, and S. Y. Chen, "Inverse scattering of two-dimensional dielectric objects buried in a lossy earth using the distorted born iterative method," IEEE Trans. Geosci. Remot. Sens., Vol. 39, No. 2, 339-346, 2001.
doi:10.1109/36.905242

12. Harada, H., D. J. N. Wall, T. Takenaka, and M. Tanaka, "Conjugate-gradient method applied to inverse scattering problem," IEEE Trans. Antennas Propagat., Vol. 43, No. 8, 784-792, 1995.
doi:10.1109/8.402197

13. Kim, Y. and H. Ling, "Through-wall human tracking with multiple doppler sensors using an artificial neural network," IEEE Trans. Antennas Propagat., Vol. 57, No. 7, 2116-2122, 2009.
doi:10.1109/TAP.2009.2021871

14. Kim, Y. and H. Ling, "Human activity classification based on micro-doppler signatures using a support vector machine," IEEE Trans. Geosci. Remot. Sens., Vol. 47, No. 5, 1328-1337, 2009.
doi:10.1109/TGRS.2009.2012849

15. Wang, F. F. and Y. R. Zhang, "A real-time through-wall detection based on support vector machine," Journal of Electromagnetic Waves and Applications, Vol. 25, No. 1, 75-84, 2011.
doi:10.1163/156939311793898396

16. Tipping, M. E., "Sparse Bayesian learning and the relevance vector machine," Journal of Machine Learning Research, Vol. 1, No. 3, 211-244, 2001.


© Copyright 2010 EMW Publishing. All Rights Reserved