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access icon free Micro-Doppler feature extraction for wideband imaging radar based on complex image orthogonal matching pursuit decomposition

  • Author(s): Ying Luo 1 ; Qun Zhang 1, 2 ; Chengwei Qiu 3 ; Song Li 4 ; Tat Soon Yeo 3
    • View affiliations
    • Affiliations: 1: Institute of Information and Navigation, Air Force Engineering University, Xi'an 710077, People's Republic of China;
      2: Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), Fudan University, Shanghai 200433, People's Republic of China;
      3: Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576;
      4: Institute of Air and Missile Defense, Air Force Engineering University, Xi'an 710051, People's Republic of China
  • Source: Volume 7, Issue 8, October 2013, p. 914 – 924
    DOI:  10.1049/iet-rsn.2012.0327 , Print ISSN 1751-8784, Online ISSN 1751-8792
© The Institution of Engineering and Technology
Received 17/11/2012, Accepted 05/05/2013, Revised 10/03/2013, Published

The micro-Doppler (m-D) features induced by targets with micro-motions provide important information for automatic radar target recognition. In this study, the m-D effect induced by rotational micro-motion in wideband radar is analysed, and an algorithm for the extraction of these m-D features is proposed. By making use of the amplitude and phase information of ‘range-slow-time image’, a dictionary with m-D signal atoms is constructed in the complex image space. The orthogonal matching pursuit algorithm in vector space is then extended to the complex image space to decompose the range-slow-time image and to extract the m-D features of the target. The proposed algorithm can extract the m-D features in the presence of migration through range cells of micro-motional scatterers, and can also work well when the sampling rate in slow-time domain is lower than the Nyquist sampling rate. Simulations are given to validate the effectiveness and robustness of the proposed method.

Inspec keywords: image recognition; Doppler radar; feature extraction; radar imaging; image matching

Other keywords: m-D feature extraction; automatic radar target recognition; Nyquist sampling rate; microDoppler feature extraction; m-D signal atoms; vector space; rotational micromotion; micromotional scatterers; range-slow-time image phase information; complex image orthogonal matching pursuit decomposition; m-D effect; range-slow-time image amplitude information; wideband imaging radar

Subjects: Image recognition; Radar equipment, systems and applications

References

    1. 1)
      • 18. Li, J., Ling, H.: ‘Application of adaptive chirplet representation for ISAR feature extraction from targets with rotating parts’, IEE Proc. Radar Sonar Navig., 2003, 150, (4), pp. 284–291 (doi: 10.1049/ip-rsn:20030729).
    2. 2)
      • 15. Li, X., Deng, B., Qin, Y.L., Wang, H.Q., Li, Y.P.: ‘The influence of target micromotion on SAR and GMTI’, IEEE Trans. Geosci. Remote Sens., 2011, 49, (7), pp. 2738–2751 (doi: 10.1109/TGRS.2011.2104965).
    3. 3)
      • 3. Chen, V.C., William, J.M., Braham, H.: ‘Micro-Doppler analysis in ISAR – review and perspectives’. Int. Radar Conf.-Surveillance for a Safer World, Bordeaux, France, October 2009, pp. 1–6.
    4. 4)
      • 9. Gao, H., Xie, L., Wen, S., Kuang, Y.: ‘Micro-Doppler signature extraction from ballistic target with micro-motions’, IEEE Trans. Aerosp. Electron. Syst., 2010, 46, (4), pp. 1969–1982 (doi: 10.1109/TAES.2010.5595607).
    5. 5)
      • 13. Zhang, Q., Yeo, T.S., Tan, H.S., Luo, Y.: ‘Imaging of a moving target with rotating parts based on the Hough transform’, IEEE Trans. Geosci. Remote Sens., 2008, 46, (1), pp. 291–299 (doi: 10.1109/TGRS.2007.907105).
    6. 6)
      • 12. Martorella, M., Homer, J., Palmer, J., et al: ‘Inverse synthetic aperture radar’, EURASIP J. Appl. Signal Process., 2006, 2006, article id 63465 pp. 1–4.
    7. 7)
      • 10. Ma, L., Liu, J., Wang, T., Li, Y., Wang, X.: ‘Micro-Doppler characteristics of sliding-type scattering center on rotationally symmetric target’, Sci China Inf. Sci., 2011, 54, (9), pp. 1957–1967 (doi: 10.1007/s11432-011-4254-3).
    8. 8)
      • 7. Kim, Y., Ling, H.: ‘Human activity classification based on micro-Doppler signatures using a support vector machine’, IEEE Trans. Geosci. Remote Sens., 2009, 47, (5), pp. 1328–1337 (doi: 10.1109/TGRS.2009.2012849).
    9. 9)
      • 19. Sparr, T., Krane, B.: ‘Micro-Doppler analysis of vibrating targets in SAR’, IEE Proc. Radar Sonar Navig., 2003, 150, (4), pp. 277–283 (doi: 10.1049/ip-rsn:20030697).
    10. 10)
      • 22. Mallat, S.G., Zhang, Z.: ‘Matching pursuits with time–frequency dictionaries’, IEEE Trans. Signal Process., 1993, 41, (12), pp. 3397–3415 (doi: 10.1109/78.258082).
    11. 11)
      • 4. Chen, V.C., Li, F., Ho, S.S., Wechsler, H.: ‘Micro-Doppler effect in radar: phenomenon, model and simulation study’, IEEE Trans. Aerosp. Electron. Syst., 2006, 42, (1), pp. 2–21 (doi: 10.1109/TAES.2006.1603402).
    12. 12)
      • 23. Donoho, D.L., Tsaig, Y., Drori, I., Starck, J.L.: ‘Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit’, IEEE Trans. Inform. Theory, 2012, 58, (2), pp. 1094–1121 (doi: 10.1109/TIT.2011.2173241).
    13. 13)
      • 1. Chen, V.C.: ‘Analysis of radar micro-Doppler signature with time-frequency transform’. Proc. Statistical Signal and Array Processing, Pocono Manor, PA, USA, 2000, pp. 463–466.
    14. 14)
      • 16. Smith, G.E., Ahmad, F., Amin, M.G.: ‘Micro-Doppler processing for ultra-wideband radar data’, Proc. SPIE, 2012, 8361, pp. 83610 L-1–83610 L-10.
    15. 15)
      • 20. Pati, Y.C., Rezaiifar, R., Krishnaprasad, P.S.: ‘Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition’. Proc. 27th Annual Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, November 1993, vol. 1, pp. 40–44.
    16. 16)
      • 8. Ghaleb, A., Vignaud, L., Nicolas, J.M.: ‘Micro-Doppler analysis of wheels and pedestrians in ISAR imaging’, IET Signal Process., 2008, 2, (3), pp. 301–311 (doi: 10.1049/iet-spr:20070113).
    17. 17)
      • 5. Thayaparan, T., Abrol, S., Riseborough, E., Stankovic, L., Lamothe, D., Duff, G.: ‘Analysis of radar micro-Doppler signatures from experimental helicopter and human data’, IET Radar Sonar Navig., 2007, 1, (4), pp. 289–299 (doi: 10.1049/iet-rsn:20060103).
    18. 18)
      • 14. Luo, Y., Zhang, Q., Qiu, C.W., Liang, X.J., Li, K.M.: ‘Micro-Doppler effect analysis and feature extraction in ISAR imaging with stepped-frequency chirp signals’, IEEE Trans. Geosci. Remote Sens., 2010, 48, (4), pp. 2087–2098 (doi: 10.1109/TGRS.2009.2034367).
    19. 19)
      • 2. Chen, V.C.: ‘Micro-Doppler effect of micro-motion dynamics: a review’, Proc. SPIE, 2003, 5102, pp. 240–249 (doi: 10.1117/12.488855).
    20. 20)
      • 11. Liu, Y., Xing, M., Sun, G., et al: ‘Echo model analyses and imaging algorithm for high resolution SAR on high-speed platform’, IEEE Trans. Geosci. Remote Sens., 2012, 50, (3), pp. 933–950 (doi: 10.1109/TGRS.2011.2162243).
    21. 21)
      • 6. Cai, C., Liu, W., Fu, J.S., Lu, L.: ‘Empirical mode decomposition of micro-Doppler signature’. Proc. Int. Conf. on Radar, Washington, USA, 2005, pp. 895–899.
    22. 22)
      • 17. Bai, X., Xing, M., Zhou, F., Lu, G., Bao, Z.: ‘Imaging of micromotion targets with rotating parts based on empirical-mode decomposition’, IEEE Trans. Geosci. Remote Sens., 2008, 46, (11), pp. 3514–3523 (doi: 10.1109/TGRS.2008.2002322).
    23. 23)
      • 21. Tropp, J.A., Gilbert, A.C.: ‘Signal recovery from random measurements via orthogonal matching pursuit’, IEEE Trans. Inform. Theory, 2007, 53, (12), pp. 4655–4666 (doi: 10.1109/TIT.2007.909108).
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