volume | PIER Journals

Abstract

Feature extraction is a challenging problem in radar target identification. In this paper we attempt to exploit the sparse property of the scattering signature with a undercomplete dictionary for target identification, and establish a feature extraction scheme based on the undercomplete dictionary. Furthermore, as an application, we present a feature vector, named as the atom dictionary feature, which is extracted from the scattering signatures over a wide-angle sector. Numerical simulation results show that the proposed atom dictionary feature can improve the performance of radar target identification due to the exploitation of the sparse property of the scattering signature.

1. Toribio, R., P. Pouliguen, and J. Saillard, "Identification of radar targets in resonance zone: E-pulse techniques," Progress In Electromagnetics Research, Vol. 43, 39-58, 2003.
doi:10.2528/PIER02100201 Google Scholar

2. Lee, J. H. and H. T. Kim, "Radar target discrimination using transient response reconstruction," Journal of Electromagnetic Waves and Application, Vol. 19, No. 5, 655-669, 2005.
doi:10.1163/1569393053305062 Google Scholar

3. Lee , J. H. and H. T. Kim, "Hybrid method for natural frequency extraction: Performance improvement using Newton-Raphson method ," Journal of Electromagnetic Waves and Applications, Vol. 19, No. 8, 1043-1055, 2005.
doi:10.1163/156939305775526061 Google Scholar

4. Wang, S., X. Guan, X. Ma, D. Wang, and Y. Su, "Calculating the poles of complex radar targets," Journal of Electromagnetic Waves and Application, Vol. 20, No. 14, 2065-2076, 2006.
doi:10.1163/156939306779322657 Google Scholar

5. Turhan-Sayan, G., "Real time electromagnetic target classification using a novel feature extraction technique with PCA-based fusion," IEEE Transaction on Antennas and Propagation, Vol. 53, 766-776, Feb. 2005.
doi:10.1109/TAP.2004.841326 Google Scholar

6. Dudley, D. G., P. A. Nielsen, and D. F. Marshall, "Ultrawideband electromagnetic target identification," Ultra-wideband, Short-pulse Electromagnetics, 457-474, Plenum, New York, 1993. Google Scholar

7. Kim, K.-T., D.-K. Seo, and H.-T. Kim, "Efficient radar target recognition using the MUSIC algorithm and invariant features ," IEEE Trans. Antennas Propag., Vol. 50, No. 3, 325-337, Mar. 2002.
doi:10.1109/8.999623 Google Scholar

8. Choi, I.-S., D.-K. Seo, J.-K. Bang, H.-T. Kim, and E. J. Rothwell, "Radar target recognition using one-dimensional evolutionary programming-based CLEAN," Journal of Electromagnetic Waves and Applications, Vol. 17, No. 5, 763-784, 2003.
doi:10.1163/156939303322226464 Google Scholar

9. Lee, C. P., D.-M. Chiang, and R. Carriere, "A GTD-based parametric model for radar scattering," IEEE Transactions on Antennas and Propagation, Vol. 43, No. 10, 1055-1066, October 1995. Google Scholar

10. McClure, M. R. and L. Carin, "Matching pursuits with a wavebased dictionary," IEEE Trans. on Signal Processing, Vol. 45, 2912-2927, December 1997.
doi:10.1109/78.650250 Google Scholar

11. Li, H. J. and S. H. Yang, "Using range profiles as feature vectors to identify aerospace targets," IEEE Trans. on Antennas Propagat., Vol. 41, 261-268, Mar. 1993.
doi:10.1109/8.233138 Google Scholar

12. Li, H. J. and V. Chiou, "Aerospace target identification-Comparison between the matching score approach and the neural network approach," Journal of Electromagnetic Waves and Applications, Vol. 7, No. 6, 873-893, 1993.
doi:10.1163/156939393X00921 Google Scholar

13. Choi, I.-S., J.-H. Lee, and H.-T. Kim, "Efficient reduction of data storage for correlative target recognition using impulse radar," Journal of Electromagnetic Waves and Applications, Vol. 15, No. 6, 745-753, 2001.
doi:10.1163/156939301X00986 Google Scholar

14. Seo, D.-K., K.-T. Kim, I.-S. Choi, and H.-T. Kim, "Wide angle radar target recognition using subclass concept ," Progress In Electromagnetics Research, Vol. 44, 231-248, 2004.
doi:10.2528/PIER03060301 Google Scholar

15. Du, L., H. W. Liu, Z. Bao, and M. D. Xing, "Radar HRRP target recognition based on higher order spectra," IEEE Trans. Signal Process, Vol. 53, 2359-2368, July 2005. Google Scholar

16. 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 Google Scholar

17. Jung, J. H., H. T. Kim, and K. T. Kim, "Comparisons of four feature extraction approaches based on Fisher's linear discriminant criterion in radar target recognition," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 2, 251-265, 2007.
doi:10.1163/156939307779378781 Google Scholar

18. Lee, K.-C., C.-W. Huang, and M.-C. Fang, "Radar target recognition by projected features of frequency-diversity RCS," Progress In Electromagnetics Research, Vol. 81, 121-133, 2008.
doi:10.2528/PIER08010206 Google Scholar

19. Champeney, D. C., A Handbook of Fourier Theorems, Cambridge University Press, 1987.

20. Mallat, S., "A theory for multiresolution signal decomposition: The wavelet decomposition," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, 674-693, July 1989. Google Scholar

21. Mallat, S. and Z. Zhang, "Matching pursuits with time-frequency dictionaries," IEEE Trans. On Signal Processing, Vol. 41, 3397-3415, Dec. 1993.
doi:10.1109/78.258082 Google Scholar

22. Engan, K. S. O. Aase and J. H. Husoy, "Method of optical directions for frame design," Proc. ICASSP, 2443-2446, Phoenix, AZ, 1999. Google Scholar

23. Wang, D., X. Ma, and Y. Su, "Radar target identification using a likelihood ratio test and matching pursuit technique," IEE Proc. Radar, Sonar and Navigation, Vol. 153, 509-515, Dec. 2006. Google Scholar

Dr. Dang-Wei Wang

Dr. Xiaoyan Ma

Dr. Yi Su