Study on Respiration Signal Detection Algorithm of Ultra-WideBand Through-wall Radar Based on A<italic/> Priori Signal-to-Noise Ratio Estimation

PAN Jun; YE Shengbo; SHI Cheng; NI Zhikang; ZHENG Zhijie; FANG Guangyou

doi:10.11999/JEIT211042

Volume 44 Issue 4

Apr. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(4): 1241-1248

PAN Jun, YE Shengbo, SHI Cheng, NI Zhikang, ZHENG Zhijie, FANG Guangyou. Study on Respiration Signal Detection Algorithm of Ultra-WideBand Through-wall Radar Based on A Priori Signal-to-Noise Ratio Estimation[J]. Journal of Electronics & Information Technology, 2022, 44(4): 1241-1248. doi: 10.11999/JEIT211042

Citation:

PAN Jun, YE Shengbo, SHI Cheng, NI Zhikang, ZHENG Zhijie, FANG Guangyou. Study on Respiration Signal Detection Algorithm of Ultra-WideBand Through-wall Radar Based on A Priori Signal-to-Noise Ratio Estimation[J]. Journal of Electronics & Information Technology, 2022, 44(4): 1241-1248. doi: 10.11999/JEIT211042

Citation:

PAN Jun, YE Shengbo, SHI Cheng, NI Zhikang, ZHENG Zhijie, FANG Guangyou. Study on Respiration Signal Detection Algorithm of Ultra-WideBand Through-wall Radar Based on A Priori Signal-to-Noise Ratio Estimation[J]. Journal of Electronics & Information Technology, 2022, 44(4): 1241-1248. doi: 10.11999/JEIT211042

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Study on Respiration Signal Detection Algorithm of Ultra-WideBand Through-wall Radar Based on A Priori Signal-to-Noise Ratio Estimation

doi: 10.11999/JEIT211042

PAN Jun^{1, 2, 3},
YE Shengbo^{1, 2},
SHI Cheng^{1, 2, 3},
NI Zhikang^{1, 2, 3},
ZHENG Zhijie^{1, 2, 3},
FANG Guangyou^{1, 2, 3
,
,}

1.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2.
Key Laboratory of Electromagnetic Radiation and Sensing Technology, Chinese Academy of Sciences, Beijing 100094, China
3.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Funds: The National Natural Science Foundation of China (61827803), The Key R&D Program of the Ministry of Science and Technology (2018YFC0810200)

Received Date: 2021-09-27
Accepted Date: 2021-12-28
Rev Recd Date: 2021-12-27

Available Online: 2022-01-23

Publish Date: 2022-04-18

Abstract

Abstract

The detection of respiration signal under the ruins is of great significance to earthquake rescue. In reality, the human respiration signal behind the obstacle (such as walls) will be masked by noise in the environment. How to improve the Signal-to-Noise Ratio (SNR) of the through-wall respiration signal is still a challenging task. A detection algorithm based on a priori SNR estimation for enhancing the output SNR of the weak through-wall respiration signal is proposed in this paper. Based on the typical Decision-Directed (DD) algorithm of spectral subtraction methods, an adaptive weighting factor is added in the proposed algorithm to eliminate further the residual random noise by reducing the estimation error of the a priori SNR. The performance of the proposed algorithm is investigated through simulation and experimental verification. The output SNR of the proposed respiration detection algorithm is improved compared with the traditional Fast Fourier Transform (FFT), Singular Value Decomposition (SVD), and DD detection algorithm.
- Through-wall radar,
- Ultra-WideBand(UWB),
- Respiration detection,
- A priori Signal-to-Noise Ratio(SNR)

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References(20)

References

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