This paper analyzes the frequency error variance of a low complexity single tone frequency estimator based on sample correlations of the input data. In the high SNR scenario it is analytically shown that the accuracy of a properly tuned algorithm is nearly optimal, i.e. nearly attains the Cramer-Rao lower bound. For low SNR the statistical efficiency of the algorithm is degraded, but it is analytically proven that for a large number of samples the error variance attains the lower bound for this class of estimators.
展开▼
