A noise-compensated long correlation matching method for AR spectral estimation of noisy signals

A noise-compensated long correlation matching (NCLCM) method is proposed for autoregressive (AR) spectral estimation of the noisy AR signals. This method first computes the AR parameters from the high-order Yule-Walker equations. Next, it employs these AR parameters and uses the low-order Yule-Walker equations to compensate the zeroth autocorrelation coefficient for the additive white noise. Finally, it solves the low- as well as high-order Yule-Walker equations in a least-squares sense to determine the AR parameters. It is shown that for the noisy AR signals the NCLCM method performs better than the conventional Burg method and the high-order Yule-Walker method.