Identification of complex autoregressive processes

The problem of estimating the spectrum of a complex stochastic process observed in additive white noise is considered. The problem is reduced to one of parameter identification by assuming an autoregressive model for the process. An algorithm for estimating these parameters is derived. Examples are presented to illustrate the use of the algorithm.