The recursive maximum likelihood algorithm for non-stationary signals

In this paper we address the problem of parametric spectral estimation for non-stationary signals. An extension of the recursive maximum likelihood (RML) algorithm which iteratively tracks the time-varying signature of the process parameters is proposed. In particular we deal with the problem of estimating the parameters of time-varying autoregressive (TVAR) processes. Computer simulations are conducted that demonstrate the performance of the new method for parameter estimation as well as for time-varying spectral estimation.