Estimation of chirp signals with time-varying amplitudes

The problem of parameters estimation of signals composed of an unknown number of chirps with time varying amplitude is presented using a sparse reconstruction framework. The method employs a parametric model using a weighted combination of splines to model the time-varying nature of the signal amplitudes. To obtain high-resolution of the frequencies and to avoid large dimensional matrices, a dictionary refinement technique is employed. The method can accurately estimate the amplitude and frequency parameters of multiple signal components, and may be extended to allow for non-linear chirps. Furthermore, an efficient implementation to solve the resulting optimization problem is proposed. Results on both synthetic and experimental signals illustrate the efficient performance of the algorithm. (C) 2018 Elsevier B.V. All rights reserved.