Interference Suppression Method of Millimeter Wave Bioradar Based on Improved Singular Spectrum Analysis

Liu Zhen-yu; Li Cheng-guang; Wang Zi-bin

doi:10.12052/gdutxb.220182

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Interference Suppression Method of Millimeter Wave Bioradar Based on Improved Singular Spectrum Analysis

更新时间：2026-05-27

- Interference Suppression Method of Millimeter Wave Bioradar Based on Improved Singular Spectrum Analysis
- Vol. 41, Issue 1, Pages: 47-54(2024)
- 作者机构：
  
  广东工业大学信息工程学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.220182
  CLC： TN959.6
- Online First：25 January 2024，
  
  Published：2024
- 稿件说明：
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刘震宇, 李成光, 王梓斌. 基于改进奇异谱分析的毫米波生物雷达干扰抑制方法[J]. 广东工业大学学报, 2024, 41(1): 47-54.

Liu Zhen-yu, Li Cheng-guang, Wang Zi-bin. Interference Suppression Method of Millimeter Wave Bioradar Based on Improved Singular Spectrum Analysis[J]. 2024, 41(1): 47-54.
刘震宇, 李成光, 王梓斌. 基于改进奇异谱分析的毫米波生物雷达干扰抑制方法[J]. 广东工业大学学报, 2024, 41(1): 47-54. DOI： 10.12052/gdutxb.220182.

Liu Zhen-yu, Li Cheng-guang, Wang Zi-bin. Interference Suppression Method of Millimeter Wave Bioradar Based on Improved Singular Spectrum Analysis[J]. 2024, 41(1): 47-54. DOI： 10.12052/gdutxb.220182.

摘要

针对毫米波雷达间的互扰会造成生物雷达获取的微弱生命体征信号被淹没，导致无法准确测量呼吸心跳的问题，本文提出基于改进奇异谱分析的方法抑制雷达间互扰，通过相关性计算从受扰信号中选取目标差拍信号重构以抑制干扰和消除背景噪声。进一步提出基于信息熵的集合经验模态分解方法消除差拍信号残留的相位噪声，通过信息熵计算从集合经验模态分解后的固有模态函数分量中选择呼吸和心跳信号以抑制残留噪声。实验结果表明，所提出的方法能有效地从受干扰的信号中恢复呼吸和心跳信号，提高呼吸和心跳的信噪比。因此，本文所提方法提高了生物雷达的抗干扰能力，增强了生物雷达的实用性。

Abstract

To solve the problem that the interference between millimeter wave radars will cause the weak vital sign signal obtained by bioradar to be submerged

resulting in the inability to accurately measure respiration and heartbeat

a method is proposed based on improved singular spectrum analysis to suppress the interference between radars

and the target beat signal is reconstructed from the interfered signal through correlation calculation to suppress the interference and eliminate the background noise. Furthermore

an ensemble empirical mode decomposition method based on information entropy is proposed to eliminate the residual phase noise of the beat signals

and the respiration and heartbeat signals are selected from the intrinsic mode function components after ensemble empirical mode decomposition through information entropy calculation to suppress the residual noise. Experimental results show that the proposed method can effectively recover the respiration and heartbeat signals from the interfered signals

and improve the signal-to-noise ratios of respiration and heartbeat. Therefore

the methods proposed in this research improve the anti-interference ability of bioradar and enhance the practicability of bioradar.

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references

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