Radar Human Gait Signal Analysis Using Short Time Fourier Transform

  • Negasa B. TeshaleEmail author
  • Dinkisa A. Bulti
  • Habib M. Hussien
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 244)


Human gait detection and identification by using radar signal is one of the recent subject of increased research area in signal processing. It has been indicated human gait information/signal is highly unusual which can be used for human detection and identification from one person to another. Most previous works related to this area extraction of features from the pace of pedestrians is only depending on the motions rhythm signal analysis and synthesis. Then Fourier transform and more recently time-frequency transforms are used to analyze the time shift/delay and identify the different parts of the human body playing part during the human movement. The analysis of the time/frequency shift usually needs to observe the process by taking a bit long time, at least long enough to get the gait signal cycle. However, the presence of several people simultaneously in the radar field of sight could involve interferences. Hence, in this paper we have been trying to use one of a powerful tool short time Fourier transform for the analysis of time-varying signals among the time frequency methods to extract some feature of human gait.


Time frequency analysis Radar signal Matlab 


  1. 1.
    Balazia, M., Plataniotis, K.N.: Human gait recognition from motion capture data in signature poses. IET Biom. 6(2), 129–137 (2017)CrossRefGoogle Scholar
  2. 2.
    Anderson, M.G.: Design of multiple frequency continuous wave radar hardware and micro-Doppler based detection and classification algorithms, Ph.D. dissertation, University of Texas at Austin, May 2008Google Scholar
  3. 3.
    Chi, W., Wang, J., Meng, M.Q.H.: A gait recognition method for human following in service robots. IEEE Trans. Syst. Man Cybern. Syst. PP(99) (2017)Google Scholar
  4. 4.
    Hornsteiner, C., Detlefsen, J.: Extraction of features related to human gait using a continuous wave radar. In: German Microwave Conference (2008)Google Scholar
  5. 5.
    Chen, V.C.: Detection and analysis of human motion by radar. In: 2008 IEEE Radar Conference, Rome, pp. 1–4 (2008)Google Scholar
  6. 6.
    Brandwood, D.: Fourier Transforms in Radar and Signal Processing. Artech house, inc., London (2003)zbMATHGoogle Scholar
  7. 7.
    Gurbuz, Z., Melvin, L., Williams, B.: Detection and identification of human targets in radar data. In: Proceedings of the SPIE, vol. 6567 (2007)Google Scholar
  8. 8.
    Ding, M., Fan, G.: Multilayer joint gait-pose manifolds for human gait motion modeling. IEEE Trans. Cybern. 45(11), 2413–2424 (2015)CrossRefGoogle Scholar
  9. 9.
    Ma, H., Liao, W.H.: Human gait modeling and analysis using a semi-Markov process with ground reaction forces. IEEE Trans. Neural Syst. Rehabil. Eng. 25(6), 597–607 (2017)CrossRefGoogle Scholar
  10. 10.
    Mahafza, B.R.: Radar Signal Analysis and Processing Using MATLAB. CRC Press, Boca Raton (2008)CrossRefGoogle Scholar
  11. 11.
    Geisheimer, J., Marshal, W., Greneker, E.: A CW radar for gait analysis. In: IEEE Conference on Signals, Systems and Computers, vol. 1, pp. 834–838 (2001)Google Scholar
  12. 12.
    Ram, S., Li, Y., Lin, A., Ling, H.: Doppler-based detection and tracking of humans in indoor environment. J. Franklin Inst. 345, 679–699 (2008)CrossRefGoogle Scholar
  13. 13.
    Seifert, A.K., Zoubir, A.M., Amin, M.G.: Radar-based human gait recognition in cane-assisted walks. In: 2017 IEEE Radar Conference (RadarConf), Seattle, WA (2017)Google Scholar
  14. 14.
    Badiezadeh, A., Ayatollahi, F., Ghaeminia, M.H., Shokouhi, S.B.: Human gait recognition using Dual-Tree Complex Wavelet Transform. In: 2017 Iranian Conference on Electrical Engineering (ICEE), Tehran, pp. 461–466 (2017)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Negasa B. Teshale
    • 1
    Email author
  • Dinkisa A. Bulti
    • 1
  • Habib M. Hussien
    • 1
  1. 1.School of Electrical and Computer Engineering Addis AbabaAddis AbabaEthiopia

Personalised recommendations