Statistically consistent frequency estimation using linear prediction

A new statistically consistent frequency estimation method has been developed and presented using linear prediction (LP) method. The observed signal is assumed to be a sum of complex exponentials with white random noise process. The number of complex exponentials is assumed to be known. A statistically consistent estimator is an estimator that converges to the true value as the number of observations increases to infinite. It is shown that conventional LP-based estimation methods such as Prony´s method are not consistent statistically. It is also proved that the new estimation method provides statistically consistent estimates and performs better than Prony´s estimation method. Numerical simulation is provided to confirm the performance of the new estimation method and its statistical consistency