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An Improved Time Frequency Analysis Method for Noisy Multi-Component Signals

Analyzing time frequency (TF) distribution of multi-component signals with noise is an important issue in signal processing of many applications. S-method (SM) is an effective multi-component TF distribution and easy to implement, but it is sensitive to noise. Aiming at the characteristics of SM, a smoothed SM (SSM) time frequency analysis method is proposed to analyze the noisy signals. SSM is a trade-off between SM and spectrogram. It balances the noise-suppression ability and resolution through adding a smooth term. The most distinguishable advantage of SSM is that it is able to process the signals at low signal-to-noise ratio (SNR) effectively. Experimental results show that SSM strengthens the signal components and decreases the noise effectively, and SSM is superior to SM at low SNR.