On the identification of AR systems excited by periodic signals of unknown phase

Results pertaining to the short and long term covariance identification of AR models driven by periodic sequences of possibly unknown phase are presented. The work is motivated by problems relating to LPC analysis of voiced speech, but results are formulated in general. Short term and asymptotic effects of such inputs on the invertibility of the covariance matrix are considered. Short term criteria with respect to the input for exact solution are established and an asymptotic bound for the case of inexact solution is developed.