Robust PCA micro-doppler classification using SVM on embedded systems

IEEE Transactions on Aerospace and Electronic Systems

Volumn 50, Issue 3, 2014, Pages 2304-2312

  Zabalza, Jaime ^a   Clemente, Carmine ^a   Di Caterina, Gaetano ^a   Ren, Jinchang ^a   Soraghan, John J ^a   Marshall, Stephen ^a  

^a UNIVERSITY OF STRATHCLYDE   (United Kingdom)

Author keywords

Digital signal processing; Feature extraction; Legged locomotion; Principal component analysis; Radar; Support vector machines; Training

Indexed keywords

DIGITAL SIGNAL PROCESSING; DIGITAL SIGNAL PROCESSORS; EMBEDDED SYSTEMS; EXTRACTION; FEATURE EXTRACTION; PERSONNEL TRAINING; RADAR; REAL TIME CONTROL; ROBUST CONTROL; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES;

FEATURE EXTRACTION TECHNIQUES; LEGGED LOCOMOTION; MICRO-DOPPLER; OUTLIER REJECTION; REAL-TIME IMPLEMENTATIONS; ROBUST PCA; ROBUST PRINCIPAL COMPONENT ANALYSIS; SUPPORT VECTOR MACHINE CLASSIFIERS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84919679896     PISSN: 00189251     EISSN: None     Source Type: Journal    
DOI: 10.1109/TAES.2014.130082     Document Type: Article

References (33)

1. Chen, V. C., Li, F., Ho, S.-S., and Wechsler, H. Micro-Doppler effect in radar: Phenomenon, model, and simulation study. IEEE Transactions on Aerospace and Electronic Systems, 42, 1 (2006), 2-21.
2. Chen, V. Micro-Doppler Effect in Radar. Norwood, MA: Artech House, 2011.
3. Clemente, C., and Soraghan, J. J. Vibrating target micro-Doppler signature in bistatic SAR with a fixed receiver. IEEE Transactions on Geoscience and Remote Sensing, 50, 8 (2012), 3219-3227.
4. Clemente, C., and Soraghan, J. J. Vibrating micro-Doppler signature extraction from SAR data using singular value decomposition. In Proceedings of the European Conference on Synthetic Aperture Radar, Nuremberg, Germany, April 2012, 191-194.
5. Clemente, C., and Soraghan, J. J. Passive bistatic radar for helicopters classification: A feasibility study. In Proceedings of the Radar Conference, Atlanta, GA, May 2012.
6. Balleri, A., Chetty, K., and Woodbridge, K. Classification of personnel targets by acoustic micro-Doppler signatures. IET Radar, Sonar and Navigation, 5, 9 (2011), 943-951.
7. Tahmoush, D., and Silvious, J. Radar micro-Doppler for long range front-view gait recognition. In Proceedings of the IEEE International Conference on Biometrics: Theory, Applications, and Systems, Washington DC, September 2009, 1-6.
8. Kim, Y., and Ling, H. Human activity classification based on micro-Doppler signatures using a support vector machine. IEEE Transactions on Geoscience and Remote Sensing, 47, 5 (2009), 1328-1337.
9. Molchanov, P., Astola, J., Egiazarian, K., and Totsky, A. Classification of ground moving radar targets by using joint time-frequency analysis. In Proceedings of the IEEE Radar Conference, Atlanta, GA, May 2012, 366-371.
10. Molchanov, P., Astola, J., Egiazarian, K., and Totsky, A. Ground moving target classification by using DCT coefficients extracted from micro-Doppler radar signatures and artificial neuron network. In Proceedings of the Microwaves, Radar and Remote Sensing Symposium, Kiev, Ukraine, August 2011, 173-176.
11. Molchanov, P. A., Astola, J. T., Egiazarian, K. O., Khlopov, G. I., Morozov, V. Y., Pospelov, B. B., and Totsky, A. V. Object recognition in ground surveillance Doppler radar by using bispectrum-based time-frequency distributions. In Proceedings of the International Radar Symposium, Vilnius, Lithuania, June 2010, 1-4.
12. Molchanov, P. O., Astola, J. T., Egiazarian, K. O., and Totsky, A. V. Moving target classification in ground surveillance radar ATR system by using novel bicepstral-based information features. In Proceedings of the European Radar Conference, Manchester, UK, October 2011, 194-197.
13. Bjorklund, S., Johansson, T., and Petersson, H. Evaluation of a micro-Doppler classification method on mm-wave data. In Proceedings of the IEEE Radar Conference, Atlanta, GA, May. 2012, 934-939.
14. Smith, G. E., Woodbridge, K., and Baker, C. J. Template based micro-Doppler signature classification. In Proceedings of the Radar Conference, Verona, NY, April 2006, 158-161.
15. Smith, G. E., Woodbridge, K., Baker, C. J., and Griffiths, H. Multistatic micro-Doppler radar signatures of personnel targets. IET Signal Processing, 4, 3 (2010), 224-233.
16. Smith, G. E., Woodbridge, K., and Baker, C. J. Radar micro-Doppler signature classification using dynamic time warping. IEEE Transactions on Aerospace and Electronic Systems, 46, 3 (2010), 1078-1096.
17. Serir, A., and Bouhafsi, Y. Micro-Doppler radar signature classification by time-frequency and time-scale analysis. In Proceedings of the International Conference on Information Science, Signal Processing and Their Applications, Montreal, Canada, July 2012, 995-1000.
18. Rousseeuw, P., and Leroy, A. Robust Regression and Outliers Detection. New York: John Wiley & Sons, 1987.
19. Rousseeuw, P. Least median of squares regression. Journal of the American Statistical Association, 79, 388 (1984), 871-880.
20. Rousseeuw, P. Multivariate Estimation with High Breakdown Point, vol. B. edited by W. Grossmann, G. Pflug, I. Vincze, and W. Werty, Reidel, Dordrecht, Netherlands, 1985.
21. Rousseeuw, P., and Driessen, K. A fast algorithm for the minimum covariance determinant estimator. Technometrics, 41, 3 (1999), 212-223.
22. Beltramonte, T., Clemente, C., di Bisceglie, D., and Galdi, C. Robust multiband detection of thermal anomalies using the minimum covariance determinant estimator. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Cape Town, South Africa, July 2009, 65-68.
23. Texas Instruments. TMS320C6713 DSK Technical Reference. Spectrum Digital, Stafford, TX, May 2003.
24. Jolliffe, I. T. Principal Component Analysis (Sprinter Series in Statistics), 2nd ed. New York: Springer-Verlag, 2002.
25. Fishman, G. S. Monte Carlo: Concepts, Algorithms and Applications. New York: Springer, 1995.
26. Chassaing, R. Digital Signal Processing and Application with the C6713 and C6416 DSK. Hoboken, NJ: John Wiley & Sons, 2005.
27. Texas Instruments. How to Write an RTDX Host Application Using MATLAB. 2002.
28. Thorsten, J. Making large-scale support vector machine learning practical. In Advances in Kernel Methods. Dortmund, Germany: MIT Press, 1999, pp. 169-184.
29. Vapnik, V. N. Statistical Learning Theory. New York: Wiley, 1998.
30. Zabalza, J., Ren, J., Clemente, C., Di Caterina, G., and Soraghan, J. J. Embedded SVM on TMS320C6713 for signal prediction in classification and regression applications. In Proceedings of the European DSP Education and Research Conference, Amsterdam, Netherlands, September, 2012.
31. Bobic, B. The database of radar echoes from various targets, http://cid-3aaf3e18829259c0.skydrive.live.com/home.aspx.
32. Andric, M. S., Bondzulic, B. P., and Zrnic, B. M. The database of radar echoes from various targets with spectral analysis. In Proceedings of the Symposium on Neural Network Applications in Electrical Engineering, Belgrade, Serbia, September 2010, 187-190.
33. Andric, M. S., Bondzulic, B. P., and Zrnic, B. M. Feature extraction related to target classification for a radar Doppler echoes. In Proceedings of the Telecommunications Forum, Belgrade, Serbia, September 2010, 725-728.