Reflection coefficient estimates based on a Markov chain model

We modify the usual lattice formulation of linear predictive analysis by using hard-limited versions of the forwards and backwards prediction error signals to compute estimates of the reflection coefficients. A four state Markov chain model is proposed for the resulting pair-process at each stage of the lattice. For a special case of the model, simple maximum likelihood estimates can be derived. The resulting estimation method reduces the sensitivity of the estimates to outliers in the observations, giving a more robust power spectrum estimate.