Cross-terms reduction in the Wigner-Ville distribution using tunable-Q wavelet transform

This paper proposes a new method to reduce cross-terms in the Wigner-Ville distribution (WVD) using tunable-Q wavelet transform (TQWT). The suggested method exploits the advantages of sub-band filtering of filter-bank and also retaining the time-resolution property of the wavelet decomposition to achieve signal decomposition. Signal components in sub-bands obtained using TQWT are further separated in time-domain using time-domain energy distribution to eliminate inner-interference terms. Simulation results for multi-component non-stationary signals are presented in order to show the efficacy of the suggested method for cross-terms reduction in WVD. Results are compared with the existing methods based on the Fourier-Bessel (FB) series expansion and filter-bank based cross-terms reduction methods in WVD, in order to show the advantages over the compared methods. HighlightsThis paper presents a new method based on TQWT for cross terms reduction in WVD.The proposed method has been studied on multi-component non-stationary signals.The simulation results have been compared with the other existing methods.The proposed method works well even in the presence of noise.