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.