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.
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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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Liang, X., Zhang, H., Lu, T. et al. An improved signal processing algorithm for VSF extraction. Multidim Syst Sign Process 30, 1811–1827 (2019). https://doi.org/10.1007/s11045-019-00629-8
- Ultra-wideband (UWB) radar
- Vital sign feature (VSF)
- Discrete windowed Fourier transform (DWFT)