A fast and accurate single frequency estimator

A novel frequency estimator for a single complex sinusoid in complex white Gaussian noise is proposed. The estimator is more computationally efficient that the optimal maximum-likelihood estimator yet attains equally good performance at moderately high signal-to-noise ratios. The estimator is shown to be related to the linear prediction estimator. This relationship is used to reveal why the linear prediction estimator does not attain the Cramer-Rao bound even at high signal-to-noise ratios.>