A novel method of micro-Doppler parameter extraction for human monitoring terahertz radar network

Human target characteristic parameter extraction is an important approach of behavior monitoring. The extraction of the characteristic can be applied in various backgrounds, such as sanatorium and hospital. Therefore, this technology is widely studied. Towards extracting physiological characteristic parameters and motion characteristic features of human target, a novel human parameter extraction algorithm is proposed in this paper which has high detection accuracy. The high accuracy detection is achieved by combining the time-frequency analysis and image processing algorithm. Besides that, the utilization of short wavelength and evident micro-motion features inherent with terahertz radar also contributes the improvement of detection accuracy. Simulations test the effectiveness of proposed the algorithm, and illustrate its performance of high extraction precision and insensitivity to noise. For comparison, the simulations are also performed in X-band radar. Via the thorough simulations, we can clearly find the advantage of our proposed algorithm in human target characteristic parameter extraction.

[1]  Eugene F. Greneker,et al.  High-resolution Doppler model of the human gait , 2002, SPIE Defense + Commercial Sensing.

[2]  Ljubisa Stankovic,et al.  Analysis of radar micro-Doppler signatures from experimental helicopter and human data , 2007 .

[3]  T. Thayaparan,et al.  Micro-Doppler Radar Signatures for Itelligent Target Recognition , 2004 .

[4]  Yong Huang,et al.  Microwave life-detection systems for searching human subjects under earthquake rubble or behind barrier , 2000, IEEE Transactions on Biomedical Engineering.

[5]  H. Wechsler,et al.  Analysis of micro-Doppler signatures , 2003 .

[6]  H. Wechsler,et al.  Micro-Doppler effect in radar: phenomenon, model, and simulation study , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[7]  J.L. Geisheimer,et al.  A continuous-wave (CW) radar for gait analysis , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[8]  Ram M. Narayanan,et al.  Hilbert-Huang Transform (HHT) Processing of Through-Wall Noise Radar Data for Human Activity Characterization , 2007 .

[9]  Melody L Massar,et al.  Time-Frequency Analysis of Terahertz Radar Signals for Rapid Heart and Breath Rate Detection , 2012 .

[10]  Daniel Thalmann,et al.  A global human walking model with real-time kinematic personification , 1990, The Visual Computer.

[11]  Philip Constantinou,et al.  Microwave system for the detection of trapped human beings , 1995, 1995 Proceedings of the IEEE International Symposium on Industrial Electronics.

[12]  Jin Li,et al.  Research on micro-feature extraction algorithm of target based on terahertz radar , 2013, EURASIP J. Wirel. Commun. Netw..

[13]  Christopher L. Vaughan,et al.  Dynamics of human gait , 1992 .

[14]  Yiming Pi,et al.  Micro-Doppler Signature Feature Analysis in Terahertz Band , 2009 .

[15]  Hao Ling,et al.  Time-Frequency Transforms for Radar Imaging and Signal Analysis , 2002 .

[16]  I. B. Shirokov,et al.  Wearable microwave autodyne sensor for monitoring of heart rhythm and breath , 2012, 2012 6th International Conference on Ultrawideband and Ultrashort Impulse Signals.