A combined Wigner-Ville and Hough transform for cross-terms suppression and optimal detection and parameter estimation

An attempt is made to show that the combined use of the Wigner-Ville distribution (WVD) and the Hough transform (HT) provides an important tool for mapping the signals onto a parameter space where the detection and parameter estimation problems can be made easier, since the important features of the signal are emphasized. This mapping can be used in the detection and parameter estimation of unknown signals embedded in noise. It is shown that this mapping comes directly from the application of the matched filter theory. In particular, the method can be applied to multicomponent signals, since it reduces considerably the effect of the cross terms, produced by the WVD, on the signal parameters estimate