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An improved signal processing algorithm for VSF extraction

  • Xiaolin LiangEmail author
  • Hao Zhang
  • Tingting Lu
  • Han Xiao
  • Guangyou Fang
  • Thomas Aaron Gulliver
Article
  • 29 Downloads

Abstract

Contactless detection of human beings via extracting vital sign features (VSF) is a perfect technology by employing an ultra-wideband radar. Only using Fourier transform, it is a challenging task to extract VSF in a complex environment, which can cause a lower signal to noise ratio (SNR) and significant errors due to the harmonics. This paper proposes an improved signal processing algorithm for VSF extraction via analyzing the skewness and standard deviation of the collected impulses. The discrete windowed Fourier transform technique is used to estimate the time of arrival of the pulses. The frequency of human breathing movements is obtained using an accumulation scheme in frequency domain, which can better cancel out the harmonics. The capabilities of removing clutters and improving SNR are validated compared with several well-known methods experimentally.

Keywords

Ultra-wideband (UWB) radar Vital sign feature (VSF) Discrete windowed Fourier transform (DWFT) 

Notes

Acknowledgements

This work was funded by the Science and Technology on Electronic Test and Measurement Laboratory (614200102010617, 614200103010117, 614200105010217), and China Electronics Technology Group Corporation Innovation Fund (KJ1701008).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Xiaolin Liang
    • 1
    • 2
  • Hao Zhang
    • 3
  • Tingting Lu
    • 3
  • Han Xiao
    • 3
  • Guangyou Fang
    • 4
  • Thomas Aaron Gulliver
    • 5
  1. 1.Science and Technology on Electronic Test and Measurement LaboratoryThe 41st Research Institute of CETCQingdaoChina
  2. 2.China Electronics Technology Instruments Co. LtdQingdaoChina
  3. 3.Department of Electronic EngineeringOcean University of ChinaQingdaoChina
  4. 4.The Key Laboratory of Electromagnetic Radiation and Sensing TechnologyChinese Academy of ScienceBeijingChina
  5. 5.Department of Electrical Computer EngineeringUniversity of VictoriaVictoriaCanada

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