Time-frequency analysis of non-stationary signals using frequency slice wavelet transform

Abstract

This paper presents a new time-frequency signal analysis method, called Frequency Slice Wavelet Transform (FSWT) for analysis of non-stationary signals. Spectral analysis using the Fourier Transform is a powerful technique for stationary time series where the characteristics of the signal do not change with time. For non-stationary time series like modulated signals, the spectral content changes with time and hence time-averaged amplitude spectrum found by using Fourier Transform is inadequate to track the changes in the signal magnitude, frequency or phase. The FSWT is an extension of short time Fourier Transform in the frequency domain and is based on a moving and scalable localizing modified Gaussian window. This transform has some desirable characteristics that are absent in the earlier wavelet transform. The Frequency Slice Wavelet Transform is unique in that it provides frequency - dependant resolution while maintaining a direct relationship with the Fourier spectrum. Several non-stationary synthetic and practical power signals are taken for analysis using both frequency slice wavelet transform and wavelet transforms to prove the superiority of the former over the later.