AR spectral estimation of segmented time signals

Abstract

The problem of estimating the power spectral density of stationary time series when the measurements are not contiguous is discussed. Two autoregressive (AR) modeling methods are proposed to handle are spectral estimation of the segmented time signals and show the statistical efficiency in numerical examples. The performance of the proposed AR method is illustrated by simulation examples. The examples indicate that the method performs satisfactorily.<>