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2010-04-13

Through -the-Wall Detection of Stationary Human Targets Using Doppler Radar

By Ram M. Narayanan, Mahesh C. Shastry, Pin-Heng Chen, and Mark Levi
Progress In Electromagnetics Research B, Vol. 20, 147-166, 2010
doi:10.2528/PIERB10022206

Abstract

In homeland security and law enforcement situations, it is often required to remotely detect human targets obscured by walls and barriers. In particular, we are specifically interested in scenarios that involve a human whose torso is stationary. We propose a technique to detect and characterize activity associated with a stationary human in through-the-wall scenarios using a Doppler radar system. The presence of stationary humans is identified by detecting Doppler signatures resulting from breathing, and movement of the human arm and wrist. The irregular, transient, non-uniform, and non-stationary nature of human activity presents a number of challenges in extracting and classifying Doppler signatures from the signal. These are addressed using bio-mechanical human arm movement models and the empirical mode decomposition (EMD) algorithm for Doppler feature extraction. Experimental results demonstrate the effectiveness of our approach to extract Doppler signatures corresponding to human activity through walls using a 750-MHz Doppler radar system.

Citation


Ram M. Narayanan, Mahesh C. Shastry, Pin-Heng Chen, and Mark Levi, "Through -the-Wall Detection of Stationary Human Targets Using Doppler Radar," Progress In Electromagnetics Research B, Vol. 20, 147-166, 2010.
doi:10.2528/PIERB10022206
http://jpier.org/PIERB/pier.php?paper=10022206

References


    1. Greneker, E. F., Radar sensing of heartbeat and respiration at a distance with security applications, Proc. SPIE Conf. Radar Sensor Technol. II, Vol. 3066, 22-27, Orlando, FL, April 1997.

    2. Greneker, E. F., Radar flashlight for through-the-wall detection of humans, Proc. SPIE Conf. Targets Backgr.: Charact. Represent. IV, Vol. 3375, 280-285, Orlando, FL, April 1998.

    3. Ahmad, F., G. J. Frazer, S. A. Kassam, and M. G. Amin, "Design and implementation of near field wideband synthetic aperture beamformer," IEEE Trans. Aerosp. Electron. Syst., Vol. 40, No. 1, 206-220, 2004.
    doi:10.1109/TAES.2004.1292154

    4. Franceschetti, G., J. Tatoian, D. Giri, and G. Gibbs, Timed arrays and their application to impulse SAR for through-the-wall imaging , IEEE Antennas Propag. Soc. Int. Symp. Dig., 3067-3070, Monterey, CA, June 2004.

    5. Nag, S., M. A. Barnes, T. Payment, and G. Holladay, "Ultrawideband through-wall radar for detecting the motion of people in real time ," Proc. SPIE Conf. Radar Sens. Technol. Data Vis., Vol. 4744, 48-57, Orlando, FL, April 2002.

    6. Attiya, A. M., A. M. Bayram, A. Safaai-Jazi, and S. M. Raid, "UWB applications for through wall detection," IEEE Antennas Propag. Soc. Int. Symp. Dig., 3079-3082, Monterey, CA, June 2004.

    7. Geisheimer, J. E., E. F. Greneker, and W. S. Marshall, "High-resolution Doppler model of the human gait," Proc. SPIE Conf. Radar Sens. Technol. Data Vis., Vol. 4744, 8-18, Orlando, FL, April 2002.

    8. Van Dorp, P. and F. C. A. Groen, "Human walking estimation with radar," IEE Proc. Radar Sonar Navig., Vol. 150, No. 5, 356-365, 2003.
    doi:10.1049/ip-rsn:20030568

    9. Falconer, D. G., R. W. Ficklin, and K. G. Konolige, "Robot-mounted through-wall radar for detecting, locating, and identifying building occupants ," Proc. IEEE Int. Conf. Robot. Autom., 1868-1875, San Fransisco, CA, July 2000.

    10. Kim, Y. and H. Ling, "Human activity classification based on micro-Doppler signatures using a support vector machine," IEEE Trans. Geosci. Remote Sens., Vol. 47, No. 5, 1328-1337, 2009.
    doi:10.1109/TGRS.2009.2012849

    11. Thayaparan, T., S. Abrol, E. Riseborough, D. Stankovic, L. Lamothe, and G. Duff, "Analysis of radar micro-Doppler signatures from experimental helicopter and human data," IEE Proc. Radar, Sonar Navig., Vol. 1, No. 4, 289-299, 2003.

    12. Ram, S. S., Y. Li, A. Lin, and H. Ling, "Doppler-based detection and tracking of humans in indoor environments," J. Franklin Inst., Vol. 345, No. 6, 679-699, 2008.
    doi:10.1016/j.jfranklin.2008.04.001

    13. Huang, N. E., Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis ," Proc. R. Soc. A, Vol. 454, No. 1971, 679-699, 1998.

    14. Lai, C.-P., R. M. Narayanan, Q. Ruan, and A. Davydov, "Hilbert-Huang transform analysis of human activities using through-wall noise and noise-like radar," IET Radar Sonar Navig., Vol. 2, No. 4, 244-255, 2008.
    doi:10.1049/iet-rsn:20070140

    15. Rilling, G. and P. Flandrin, On the influence of sampling on the empirical mode decomposition, Proc. Int. Conf. Acoust. Speech Signal Process., Vol. 3, 444-447, Toulouse, France, May 2006.

    16. Heydarian, M. and J. D. Reiss, "Extraction of long-term structures in musical signals using the empirical mode decomposition," Proc. 8th Int. Conf. on Digit. Audio Eff., 258-261, Madrid, Spain, September 2005.

    17. Kamath, V., Y.-C. Lai, L. Zhu, and S. Urval, Empirical mode decomposition and blind source separation methods for antijamming with GPS signals , IEEE/ION Position Location Navig. Symp., Vol. 1, 335-341, San Diego, CA, April 2006.

    18. Camp, J. B., J. K. Cannizzo, and K. Numata, "Application of the Hilbert-Huang transform to the search for gravitational waves," Phys. Rev. D, Vol. 75, No. 6, 061101.1-5, 2007.

    19. Zhang, R. R., S. Ma, and S. Hartzell, "Signatures of the seismic source in EMD-based characterization of the 1994 Northridge, California earthquake recordings," Bull. Seismol. Soc. Am., Vol. 93, No. 1, 501-518, 2003.
    doi:10.1785/0120010285

    20. Flandrin, P., G. Rilling, and P. Goncalves, "Empirical mode decomposition as a filter bank," IEEE Signal Process. Lett., Vol. 11, No. 2, 112-114, 2004.
    doi:10.1109/LSP.2003.821662

    21. Rilling, G. and P. Goncalves, EMD Toolbox for MATLAB, http://perso.ens-lyon.fr/patrick.flandrin/emd.html, 2008.

    22. Ram, S. S. and H. Ling, "Micro-Doppler signature simulation of computer animated human and animal motions," IEEE Antennas Propag. Soc. Int. Symp. Dig., 679-699, San Diego, CA, July 2008.

    23. Atkeson, C. and J. Hollerbach, "Kinematic features of unrestrained vertical arm movements," J. Neurosci., Vol. 5, No. 1, 2318-2330, 1985.

    24. Hollerbach, J. and T. Flash, "Dynamic interactions between limb segments during planar arm movement," Biol. Cybern., Vol. 44, No. 1, 67-77, 1983.
    doi:10.1007/BF00353957

    25. Choi, H. and W. J. Williams, "Improved time-frequency representation of multicomponent signals using exponential kernels," IEEE. Trans. Acoust. Speech Signal Process., Vol. 37, No. 6, 862-871, 1989.
    doi:10.1109/ASSP.1989.28057

    26. Chen, P.-H., R. M. Narayanan, C. P. Lai, and A. Davydov, Through wall ranging and imaging using UWB random noise waveform: System design considerations and preliminary experimental results, IEEE Antennas Propag. Soc. Int. Symp. Dig., doi: 10.1109/APS.2009.5172369, Charleston, SC, June 2009.