http://iet.metastore.ingenta.com
1887

Analysis of radar micro-Doppler signatures from experimental helicopter and human data

Analysis of radar micro-Doppler signatures from experimental helicopter and human data

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Radar, Sonar & Navigation — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This paper highlights the extraction of micro-Doppler (m-D) features from radar signal returns of helicopter and human targets using the wavelet transform method incorporated with time-frequency analysis. In order for the extraction of m-D features to be realised, the time domain radar signal is decomposed into a set of components that are represented at different wavelet scales. The components are then reconstructed by applying the inverse wavelet transform. After the separation of m-D features from the target's original radar return, time-frequency analysis is then used to estimate the target's motion parameters. The autocorrelation of the time sequence data is also used to measure motion parameters such as the vibration/rotation rate. The findings show that the results have higher precision after the m-D extraction rather than before it, since only the vibrational/rotational components are employed. This proposed method of m-D extraction has been successfully applied to helicopter and human data.

References

    1. 1)
      • V.C. Chen , H. Ling . (2002) Time-frequency transform for radar imaging and signal analysis.
    2. 2)
      • Chen, V.C.: `Analysis of radar micro-Doppler signature with time frequency transform', Proc. Tenth IEEE Workshop on Statistical Signal and Array Processing, 2000, p. 463–466.
    3. 3)
      • J. Li , H. Ling . Application of adaptive chirplet representation for ISAR feature extraction from targets with rotating parts. IEE Proc., Radar Sonar Navig. , 4 , 284 - 291
    4. 4)
      • T. Sparr , B. Krane . Micro-Doppler analysis of vibrating targets in SAR. IEE Proc., Radar Sonar Navig. , 4 , 277 - 283
    5. 5)
      • T. Thayaparan . (2004) Micro-Doppler radar signatures for intelligent target recognition.
    6. 6)
      • T. Thayaparan , S. Abrol . (2005) Micro-Doppler analysis of rotating target in SAR.
    7. 7)
    8. 8)
      • Greneker, G., Geisheimer, J., Asbell, D.: `Extraction of micro-Doppler from vehicle target at X-band frequency', Proc. SPIE on Radar Technology, 2001, 4374.
    9. 9)
      • R.J. Wellman , J.L. Silvious . (1998) Doppler signature measurements of an Mi-24 Hind-D helicopter at 92 GHz, ARL-TR-1637.
    10. 10)
    11. 11)
      • Sommer, H., Salerno, J.: `Radar target identification system', U.S. Patent 3, 1971, p. 614–779.
    12. 12)
      • Tremblay, F.: `Generalization of the DREO radar jet engine modulation algorithm', DREO TR 1995-1199, 1995.
    13. 13)
      • P. van Dorp , F.C.A. Groen . Human walking estimation with radar. IEE Proc., Radar Sonar Navig. , 5 , 356 - 365
    14. 14)
      • J.L. Geisheimer , E.F. Greneker , W.S. Marshall . (2002) A high-resolution Doppler model of human gait.
    15. 15)
      • J.J. Little , J.E. Boyd . Recognizing people by their gait: the shape of motion. J. Computer Vision Res. , 2 , 1 - 32
    16. 16)
      • S.A. Niyogi , E.H. Adelson . Analyzing and recognizing walking figures in XYT. IEEE Proc. on Computer Vision Pattern Recognit , 469 - 474
    17. 17)
      • A.M. Sabatini , V. Colla . A method for sonar based recognition of walking people. Robot. Autonomous Syst. , 117 - 126
    18. 18)
      • Weir, R.F., Childress, D.S.: `A new method of characterizing gait using a potable, real-time, ultrasound ranging device', Proc. 19th Int. Conf, 1997, IEEE Engineering in Medicine and Biology Society, p. 1810–1812.
    19. 19)
      • A. Yasotharan , T. Thayaparan . Strengths and limitations of the Fourier method for detecting accelerating targets by pulse Doppler radar. IEE Proc., Radar Sonar Navig. , 2 , 83 - 88
    20. 20)
      • L. Cohen . (1995) Time-frequency analysis.
    21. 21)
      • T. Thayaparan , G. Lampropoulos , S.K. Wong , E. Riseborough . Application of adaptive time-frequency algorithm for focusing distorted ISAR images from simulated and measured radar data. IEE Proc., Radar Sonar Navig. , 4 , 213 - 220
    22. 22)
      • T. Thayaparan , S. Kennedy . Detection of a maneuvering air target in sea-clutter using joint time-frequency analysis techniques. IEE Proc., Radar Sonar Navig. , 1 , 11 - 18
    23. 23)
      • G. Lampropoulos , T. Thayaparan , N. Xie . Fusion of time-frequency distributions and applications to radar signals. J. Electron. Imaging , 2 , 1 - 17
    24. 24)
    25. 25)
      • M. Misiti , Y. Misiti , G. Oppenheim , J.-M. Poggi . (2002) Wavelet Tool-box.
    26. 26)
      • Martin, J., Mulgrew, B.: `Analysis of theoretical radar return signal from aircraft propeller blades', IEEE 1990 Int. Radar Conf., 1990, p. 569–572.
    27. 27)
      • Marple, S.L.: `Large dynamics range time-frequency signal analysis with application to helicopter Doppler radar data', ISPA Conf., 2001.
    28. 28)
      • Zediker, M.S., Rice, R.R., Hollister, J.H.: `Method for extending range and sensitivity of a fiber optic micro-Doppler system and apparatus therefore', U.S. Patent 6,847,817, December 1998.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rsn_20060103
Loading

Related content

content/journals/10.1049/iet-rsn_20060103
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address