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 HilbertHuang 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.