超声多普勒血流自小波相关分析及STFT方法的对比研究

论文阐述了短时傅里叶变换(STFT)在分析长时间非平稳随机血流信号时产生的误差,提出了一种用于超声多普勒血流信号分析的自小波相关分析(AWCA)方法.小波变换灵活可变的时频窗,在分析多普勒血流信号时更具有优势.文中给出了超声多普勒血流仿真信号,并用此信号进行了相应的短时傅里叶与自小波相关的结果分析.对比分析结果表明,自小波相关分析方法不仅适合于分析具有非平稳性的多普勒血流信号,而且能够提供更好的位置和频率分辨特性.

Comparison Research of Auto-Wavelet Correlation Analysis with STFT for Ultrasonic Doppler Blood Measurement

Short time Fourier Transform(STFT) of Doppler spectrum analysis has provide a effective lossless detecting means for blood velocity measurement and diagnosis of artery strait disease in the past.There must be analysis error using the transform for long interval unsteady blood fluid signals.Due to variable flexible spatio-temporal windows,wavelet has much more predominance when analyzing Doppler blood signals.An innovative auto-wavelet correlation analysis(AWCA) method is put forward here,which can be used in analysis of Doppler blood signals.It is given the simulative experimental signals and the analysis results,compared AWCA with STFT at last.The results indicate that AWCA method not only adapts to analyze unsteady Doppler blood signals,it can also provide better resolution properties of position and frequency.