MMSE parameter estimation of multiple chirp signals

We propose an iterative algorithm for minimum mean square error (MMSE) estimation of the parameters of multiple superimposed linear chirp signals in white Gaussian noise. The parameter estimation of each chirp component is carried out by two dimensional integration. The integrals are derived with the assumption that the remaining chirp signals have parameters whose values are fixed at their current estimates. The necessary parameter initializations are obtained by tracking the Choi-Williams (1989) time-frequency distribution and applying the least-squares method. Computer simulations provide a comparison between our scheme and the alternating projection (AP) method.