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http://dx.doi.org/10.5515/KJKIEES.2014.25.6.700

Extraction of the JEM Component in the Observation Range of Weakly Present JEM Based on Complex EMD  

Park, Ji-Hoon (Department of Electronic Engineering, Korea Advanced Institute of Science and Technology, KAIST)
Yang, Woo-Yong (Department of Electronic Engineering, Korea Advanced Institute of Science and Technology, KAIST)
Bae, Jun-Woo (Samsung Thales Ltd.)
Kang, Seong-Cheol (Department of Electronic Engineering, Korea Advanced Institute of Science and Technology, KAIST)
Kim, Chan-Hong (Agency for Defense Development)
Myung, Noh-Hoon (Department of Electronic Engineering, Korea Advanced Institute of Science and Technology, KAIST)
Publication Information
Abstract
Jet engine modulation(JEM) is a frequency modulation phenomenon of the radar signal induced by electromagnetic scattering from a rotating jet engine turbine. Although JEM can be used as a representative radar target recognition method by providing unique information on the target, its recognition performance may be degraded in the observation range of weakly present JEM. Hence, this paper presents a method for extracting the JEM component by decomposing the radar signal into intrisic mode functions(IMFs) via complex empirical mode decomposition(CEMD) and by combining them based on signal eccentricity. Its application to various signals demonstrated that the proposed method improved the clarity of JEM analysis and could extend the effective observation range of JEM.
Keywords
Complex Empirical Mode Decomposition; Jet Engine Modulation; Radar Target Recognition; Signal Eccentricity;
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  • Reference
1 M. R. Bell, R. A. Grubbs, "JEM modeling and measurement for radar target identification", IEEE Trans. Aerosp. Electron. Syst., vol. 29, no. 1, pp. 73-87, Jan. 1993.   DOI   ScienceOn
2 H. Lim, J. H. Park, J. H. Yoo, C. H. Kim, K. I. Kwon, and N. H. Myung, "Joint time-frequency analysis of radar micro-Doppler signatures from aircraft engine models", J. of Electromagn. Waves and Appl., vol. 25, pp. 1069-1080, 2011.   DOI   ScienceOn
3 T. Thayaparan, S. Abrol, E. Riseborough, L. Stankovic, D. Lamothe, and G. Duff, "Analysis of radar micro-Doppler signatures from experimental helicopter and human data", IET Radar Sonar Navig., vol. 1, no. 4, pp. 289- 299, Aug. 2007.   DOI   ScienceOn
4 G. Rilling, P. Flandrin, P. Goncalves, and J. Lilly, "Bivariate empirical mode decomposition", IEEE Signal Process. Lett., vol. 14, pp. 936-939, Dec. 2007.   DOI   ScienceOn
5 A. Ahrabian, N. Rehman, and D. Mandic, "Bivariate empirical mode decomposition for unbalanced real-world signals", IEEE Signal Process. Lett., vol. 20, pp. 245- 248, Mar. 2013.   DOI   ScienceOn
6 Q. Zhang, T. S. Yeo, H. S. Tan and Y. Luo, "Imaging of a moving target with rotating parts based on the Hough transform", IEEE Trans. Geosci. Remote Sens., vol. 46, pp. 291-299, Jan. 2008.   DOI   ScienceOn
7 G. Rilling, P. Flandrin, "One or two frequencies? The empirical mode decomposition answers", IEEE Trans. Signal Process,. vol. 56, pp. 85-95, Jan. 2008.   DOI   ScienceOn
8 J. H. Park, H. Lim, and N. H. Myung, "Analysis of jet engine modulation effect with extended Hilbert-Huang transform", IET Electron. Lett., vol. 49, no. 1, pp. 215- 216, Jan. 2013.   DOI   ScienceOn