基于虚拟仪器的生命信号小波变换分析技术

Wavelet transform of life singnal based on virtual instrument technology

本文研究小波变换多分辨率分析及阈值去噪方法在微弱生命信号提取方面的应用。基于虚拟仪器技术的软、硬件平台,搭建雷达波生命信号探测系统,实现仪器的控制和信号分析处理。根据微动多普勒频移原理,经过人体微动调制后的雷达回波信号中持有生命特征参数。通过对回波信号的分析,能检测生命体的存在。本文利用小波变换对强背景噪声下的微弱生命信号进行去噪滤波,达到低频生命信号提取的目的。在实际测试过程中,系统能快速的反应出生命迹象。提取出的信号群延迟小,曲线平稳光滑。通过不同频段的信号提取发现,生命信号主要集中在15Hz以内,并且呼吸、心跳和体动在该频段内被有效提取。利用小波变换的低频分析特性能在呼吸、心跳和体动信号的提取方面有很好的效果。

This paper focuses on the weak life signal detection and extraction with wavelet mufti-resolution analysis and threshold denoise method. Based on the virtual instrument technology, a radar life detection system is built to control the instrument and analyse the signal. According to doppler shift theory, radar signal will have life features after modulation by body micro movements. With analysis of the signal, Life can be detected. Wavelet transformation is applied in the denoise of weak life signal from strong background noise to extract the low frequency signals. In the actual test, life signal responds quickly with a smooth curve and has low group delay. After signal extraction from different frequency bands, we find that life signals concentrate within 15 Hz,and signals related to breathing,heartbeat, and movements can be abstracted effectively in this frequency band. Low frequency feature of wavelet transform has advantages in extracting breathing, heartbeat and body movement signals.