Iterative autoregressive parameter estimation in presence of additive white noise

An improved autoregressive spectral estimator in the presence of additive white noise is presented. The proposed algorithm is based on cancelling the spectral zeros through iterations. Simulation results indicate that a significant decrease in the bias and variance of the autoregressive spectral estimator may be achieved at the expense of some additional computation.