Multicomponent chirp signal parameter estimation via sparse representation

Here,a novel algorithm for parameter estimation of multicomponent chirp signal in complicated noise environment was proposed.Using the matching pursuit algorithm,the signal was firstly decomposed into Gabor atoms which provided sparse information representing the signal time-frequency feature.Hough transformation was then directly used to estimate chirp rate,starting frequency and stopping frequency of chirp components without computing the time-frequency distribution.Simulation results showed that this algorithm is capable of estimating parameters of multicomponent chirp signal,even in the presence of powerful intended interference and colored noise;comparing to other techniques,the algorithm is computationally efficient and possible to be used in real-life problems.