Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Balazia, M., Plataniotis, K.N.: Human gait recognition from motion capture data in signature poses. IET Biom. 6(2), 129–137 (2017)
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 2008
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)
Hornsteiner, C., Detlefsen, J.: Extraction of features related to human gait using a continuous wave radar. In: German Microwave Conference (2008)
Chen, V.C.: Detection and analysis of human motion by radar. In: 2008 IEEE Radar Conference, Rome, pp. 1–4 (2008)
Brandwood, D.: Fourier Transforms in Radar and Signal Processing. Artech house, inc., London (2003)
Gurbuz, Z., Melvin, L., Williams, B.: Detection and identification of human targets in radar data. In: Proceedings of the SPIE, vol. 6567 (2007)
Ding, M., Fan, G.: Multilayer joint gait-pose manifolds for human gait motion modeling. IEEE Trans. Cybern. 45(11), 2413–2424 (2015)
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)
Mahafza, B.R.: Radar Signal Analysis and Processing Using MATLAB. CRC Press, Boca Raton (2008)
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)
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)
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)
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)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Teshale, N.B., Bulti, D.A., Hussien, H.M. (2018). Radar Human Gait Signal Analysis Using Short Time Fourier Transform. In: Mekuria, F., Nigussie, E., Dargie, W., Edward, M., Tegegne, T. (eds) Information and Communication Technology for Development for Africa. ICT4DA 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 244. Springer, Cham. https://doi.org/10.1007/978-3-319-95153-9_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-95153-9_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-95152-2
Online ISBN: 978-3-319-95153-9
eBook Packages: Computer ScienceComputer Science (R0)