Transient Signal Detection Using Wigner-Ville Distribution and Wavelet Denoising

Abstract

The problem of detecting an unknown transient signal in noise is considered. The SNR of the observed data is first enhanced using wavelet domain filter. The output of the wavelet domain filter is then transformed using a Wigner-Ville transform, which separates the spectrum of the observed signal into narrow frequency bands. Each subband signal at the output of the Wigner-Ville block is subjected to wavelet based level dependent denoising (WBLDD) to supress colored noise. A weighted sum of the absolute value of outputs of WBLDD is passed through an energy detector, whose output is used as test statistic to take the final decision. By assigning weights proportional to the energy of the corresponding subband signals, the proposed detector approximates a frequency domain matched filter. Simulation results are presented to show that the performance of the proposed detector is better than that of the wavelet packet transform based detector