Vol. 1
Latest Volume
All Volumes
PIERM 130 [2024] PIERM 129 [2024] PIERM 128 [2024] PIERM 127 [2024] PIERM 126 [2024] PIERM 125 [2024] PIERM 124 [2024] PIERM 123 [2024] PIERM 122 [2023] PIERM 121 [2023] PIERM 120 [2023] PIERM 119 [2023] PIERM 118 [2023] PIERM 117 [2023] PIERM 116 [2023] PIERM 115 [2023] PIERM 114 [2022] PIERM 113 [2022] PIERM 112 [2022] PIERM 111 [2022] PIERM 110 [2022] PIERM 109 [2022] PIERM 108 [2022] PIERM 107 [2022] PIERM 106 [2021] PIERM 105 [2021] PIERM 104 [2021] PIERM 103 [2021] PIERM 102 [2021] PIERM 101 [2021] PIERM 100 [2021] PIERM 99 [2021] PIERM 98 [2020] PIERM 97 [2020] PIERM 96 [2020] PIERM 95 [2020] PIERM 94 [2020] PIERM 93 [2020] PIERM 92 [2020] PIERM 91 [2020] PIERM 90 [2020] PIERM 89 [2020] PIERM 88 [2020] PIERM 87 [2019] PIERM 86 [2019] PIERM 85 [2019] PIERM 84 [2019] PIERM 83 [2019] PIERM 82 [2019] PIERM 81 [2019] PIERM 80 [2019] PIERM 79 [2019] PIERM 78 [2019] PIERM 77 [2019] PIERM 76 [2018] PIERM 75 [2018] PIERM 74 [2018] PIERM 73 [2018] PIERM 72 [2018] PIERM 71 [2018] PIERM 70 [2018] PIERM 69 [2018] PIERM 68 [2018] PIERM 67 [2018] PIERM 66 [2018] PIERM 65 [2018] PIERM 64 [2018] PIERM 63 [2018] PIERM 62 [2017] PIERM 61 [2017] PIERM 60 [2017] PIERM 59 [2017] PIERM 58 [2017] PIERM 57 [2017] PIERM 56 [2017] PIERM 55 [2017] PIERM 54 [2017] PIERM 53 [2017] PIERM 52 [2016] PIERM 51 [2016] PIERM 50 [2016] PIERM 49 [2016] PIERM 48 [2016] PIERM 47 [2016] PIERM 46 [2016] PIERM 45 [2016] PIERM 44 [2015] PIERM 43 [2015] PIERM 42 [2015] PIERM 41 [2015] PIERM 40 [2014] PIERM 39 [2014] PIERM 38 [2014] PIERM 37 [2014] PIERM 36 [2014] PIERM 35 [2014] PIERM 34 [2014] PIERM 33 [2013] PIERM 32 [2013] PIERM 31 [2013] PIERM 30 [2013] PIERM 29 [2013] PIERM 28 [2013] PIERM 27 [2012] PIERM 26 [2012] PIERM 25 [2012] PIERM 24 [2012] PIERM 23 [2012] PIERM 22 [2012] PIERM 21 [2011] PIERM 20 [2011] PIERM 19 [2011] PIERM 18 [2011] PIERM 17 [2011] PIERM 16 [2011] PIERM 14 [2010] PIERM 13 [2010] PIERM 12 [2010] PIERM 11 [2010] PIERM 10 [2009] PIERM 9 [2009] PIERM 8 [2009] PIERM 7 [2009] PIERM 6 [2009] PIERM 5 [2008] PIERM 4 [2008] PIERM 3 [2008] PIERM 2 [2008] PIERM 1 [2008]
2008-02-06
Undercomplete Dictionary-Based Feature Extraction for Radar Target Identification
By
Progress In Electromagnetics Research M, Vol. 1, 1-19, 2008
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.
Citation
Dang-Wei Wang, Xiaoyan Ma, and Yi Su, "Undercomplete Dictionary-Based Feature Extraction for Radar Target Identification," Progress In Electromagnetics Research M, Vol. 1, 1-19, 2008.
doi:10.2528/PIERM08012805
References

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

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

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

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

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

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.

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

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

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.

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

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

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

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

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

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.

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

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

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

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.

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

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

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.