Estimation of running frequency spectra using a Kalman filter algorithm

A method is suggested for the computation of running frequency spectra from non-stationary oscillations in a long time series. The method is based on an autoregressive model where the coefficients are assumed to vary slowly. The coefficients are updated using the Kalman filter technique. The method is shown to be superior to ordinary autoregressive spectral estimation based on stationary theory in recognizing rapid changes in the frequencies of oscillations.