A Time-varying Filtering Algorithm based on Short-time Fractional Fourier Transform
Longwen Wu, Yaqin Zhao, Liang He, Shengyang He, Guanghui Ren · 2020 International Conference on Computing, Networking and Communications (ICNC) · 2020
This paper presents a novel time-varying filtering (TVF) algorithm based on order time-varying short-time fractional Fourier transform (OTV-STFrFT) for multi-component signal analysis, which can process non-linear frequency modulated (NLFM). The idea of combining TVF and the order time-varying STFrFT are mainly inspired by the following two aspects: i) NLFM signals can be locally regarded as segmented linear frequency modulated (LFM) signals; ii) the fractional Fourier transform is the optimal sparse representation of LFM signal. The order time-varying STFrFT can overcome several defects of the existing TVF algorithms in dealing with multicomponent signals, of which the mixed components may intersect in the time-frequency distribution. The numerical results shows that the proposed algorithm is superior to the TVF algorithms based on conventional short-time Fourier transform (STFT) and state-of-the-art synchrosqueezed wavelet transforms (SsWT) in multi-component signal analysis.