Novel Method for Non-stationary Signals Via High-Concentration Time-Frequency Analysis Using SSTFrFT

摘要

The short-time fractional Fourier transform (STFrFT) is beneficial for addressing non-stationary signals in many application settings. However, the STFrFT algorithm fails to obtain a high time-frequency (TF) concentration because of the uncertainty principle. To resolve these problems, we introduce a new algorithm that is referred to as the SSTFrFT, which is a combination of the synchroextracting transform and STFrFT. The main principle of this algorithm is to establish a synchroextracting operator based on the STFrFT and then to extract the TF coefficient of the ridgeline position in the TF distribution to improve the concentration. Using numerical simulations with two examples (linear frequency modulation signal and nonlinear frequency modulation signal), we illustrate how the algorithm can be useful in improving concentration. The instantaneous frequency estimation and energy distribution description are more accurate than traditional methods, such as the short-time Fourier transform, Wigner Ville distribution, synchrosqueezed transform, and STFrFT. Furthermore, we apply the algorithm to identify the frequency curve generated by the target's motion from Ice Multiparameter Imaging X-Band radar echo data from the sea clutter background. The test results of the SSTFrFT method that we developed can accurately distinguish moving targets and sea clutter, which suggest the possible utility of this approach for detection and motion characteristics of marine moving targets.