Research and Comparison of Time-frequency Techniques for Nonstationary Signals

Most of signals in engineering are nonstationary and time-varying. The Fourier transform as a traditional approach can only provide the feature information in frequency domain. The time-frequency techniques may give a comprehensive description of signals in time-frequency planes. Based on some typical nonstationary signals, five time-frequency analysis methods, i.e., the short-time Fourier transform (STFT), wavelet transform (WT), Wigner-Ville distribution (WVD), pseudo-WVD (PWVD) and the Hilbert-Huang transform (HHT), were performed and compared in this paper. The characteristics of each method were obtained and discussed. Compared with the other methods, the HHT with a high time-frequency resolution can clearly describe the rules of the frequency compositions changing with time, is a good approach for feature extraction in nonstationary signal processing.