Recognition of time-varying signals in the time-frequency domain by means of the Wigner distribution

Among the time-frequency distributions, the Wigner distribution (WD) is found to be one of the most powerful tools for time-frequency analysis. We have therefore developed an interactive simulator for time-frequency analysis based on a discrete version of the WD. The WD behavior is then studied for any frequency modulated and time limited signal. The properties of the WD make possible the detection of time-varying signals in the time-frequency domain. An application is presented where the problem is to automatically detect moving bubbles formed in the human blood under hyperbaric environments. We show that time-frequency analysis by means of the WD is an appropriate method to discriminate the bubble signals from the noise. We present some of our results.