FREQUENCY ESTIMATION BY LINEAR PREDICTION.

The application of linear prediction to frequency estimation for sinusoidal signals in noise is investigated. It is shown that improved performance is obtained by processing a complex-valued version of the real-valued input signal, with the corresponding sampling rate reduced by one-half. The case of a single sinusoid in white noise is studied in detail, including the eigenvalues of the covariance matrix, zeros of the inverse filter polynomial, frequency bias, and frequency variance as a function of input SNR and prediction order