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We presented a novel Fourier-Bessel(FB)series and Wigner-Hough transform(WHT) method for the analysis of multi-component non-stationary signals.The FB series decomposed multi-component nonstationary signals into mono-component signals. The Wigner-Ville distribution(WVD) was applied to each mono-component signal to analyze its time-frequency distribution(TFD). Summing up the WVDs of the individual components resulted in TFDs of the multicomponent signals, where the cross terms and noise were significantly reduced. The Hough transform(HT)was applied on the TFD of the multi-component signal(obtained from FB-WVD). The HT provides an important tool for mapping the signals onto a parameter space where the detection and estimation problems are made easier. This mapping can be used in the detection and parameter estimation of signals which are unknown and embedded in noise.
We present a novel Fourier-Bessel (FB) series and Wigner-Hough transform (WHT) method for the analysis of multi-component non-stationary signals. The FB series decomposed multi-component nonstationary signals into mono- Ville distribution (WVD) was applied to each mono-component signal to analyze its time-frequency distribution (TFD). Summing up the WVDs of the individual components resulted in TFDs of the multicomponent signals, where the cross terms and noise were significantly reduced. The Hough transform (HT) was applied on the TFD of the multi-component signal (obtained from FB-WVD). The HT provides an important tool for mapping the signals onto a parameter space where the detection and estimation problems are made easier. mapping can be used in the detection and parameter estimation of signals which are unknown and embedded in noise.