A Generalized Weighted Linear Predictor Frequency Estimation Approach for a Complex Sinusoid

摘要

Based on linear prediction and weighted least squares, three simple iterative algorithms for frequency estimation of a complex sinusoid in additive white noise are devised. The proposed approach, which utilizes the first-order as well as higher order linear prediction terms simultaneously but does not require phase unwrapping, can be considered as a generalized version of the weighted linear predictor frequency estimator. In particular, convergence as well as mean and variance analysis of the most computationally efficient frequency estimator, namely, GWLP 2, are provided. Computer simulations are included to contrast the performance of the proposed algorithms with several conventional computationally attractive frequency estimators and Cramer-Rao lower bound for different frequencies, observation lengths, and signal-to-noise ratios.