Multi-spectra synchrosqueezing transform

The synchrosqueezing transform (SST) is an effective method to obtain a clear time-frequency representation (TFR). Unfortunately, it suffers from low time-frequency (TF) resolution faced with strongly frequency-modulated signals, such as chirp signals. In this paper, we propose the generalized synchrosqueezing fractional S-transform (GSSFrST) to address this deficiency. In addition, we have also considered its second-order version to further enhance the TFR. They combine the advantages of fractional Fourier transform and synchrosqueezing generalized S-transform to improve the TF concentration. To further improve the TF resolution, we propose the multi-spectra synchrosqueezing transform (MSST) based on the GSSFrST and Hough transform. Inspired by the idea of image fusion, the MSST uses multiple TF spectra to fuse into a novel TF spectrum to represent each component of the signal in more detail. The experimental results show that MSST is a promising TF analysis tool for cross chirp signal separation and instantaneous frequency estimation.