The aim of this work is to propose a method for detection and parameter estimation of nonlinear FM signals, mono- or multicomponent, embedded in white Gaussian noise. The proposed approach consists in mapping the signal into the time-frequency plane hy a time-frequency distribution with reassignment, and then in applying a pattern recognition technique, like the Hough transform, to the time-frequency representation to recognize specific shapes. The advantages of this method over the conventional maximum likelihood estimator are 1) a simpler implementation, because it reduces the dimension of the search space and 2) a consistent attenuation of the interference terms between different components of a signal or between signal and noise.
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|Titolo:||Analysis of nonlinear FM signals by pattern recognition of their time-frequency representation|
|Data di pubblicazione:||1996|
|Citazione:||Analysis of nonlinear FM signals by pattern recognition of their time-frequency representation / Barbarossa, Sergio; O., Lemoine. - In: IEEE SIGNAL PROCESSING LETTERS. - ISSN 1070-9908. - 3:4(1996), pp. 112-115.|
|Appartiene alla tipologia:||01a Articolo in rivista|