Adaptive Short-time Fourier Transform and Synchrosqueezing Transform for Non-stationary Signal Separation

12/29/2018
by   Lin Li, et al.
0

The synchrosqueezing transform, a kind of reassignment method, aims to sharpen the time-frequency representation and to separate the components of a multicomponent non-stationary signal. In this paper, we consider the short-time Fourier transform (STFT) with a time-varying parameter. Based on the local approximation of linear frequency modulation mode, we analyze the well-separated condition of non-stationary multicomponent signals with this type STFT. In addition we propose the STFT-based synchrosqueezing transform (FSST) with a time-varying parameter, named the adaptive FSST, to enhance the time-frequency concentration and resolution of a multicomponent signal, and to separate its components more accurately. We also propose the 2nd-order adaptive FSST to further improve the adaptive FSST for the non-stationary signals with fast-varying frequencies. Furthermore, we present a localized optimization algorithm based on our well-separated condition to estimate the time-varying parameter adaptively and automatically. We also provide simulation results on synthetic signals and the bat echolocation signal to demonstrate the effectiveness and robustness of the proposed method.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset