Modeling of time-varying Instanteous Frequency in a finitely correlated environment

A TVAR model has been shown to perform well when applied to short data records for instantaneous frequency (IF) estimation of frequency modulated (FM) components in white noise. However, when the model is applied to a signal containing a finitely correlated signal in addition to the white noise, estimation performance degrades; especially when the correlated signal is not weak relative to the FM components. We extend the time-varying autoregressive (TVAR) model-based IF estimation for a finitely correlated environment by introducing a decorrelation delay larger than one between the time-varying coefficients. Comparison of the decorrelating TVAR based IF estimator to a conventional TVAR based IF estimator reveals performance gains at moderate to high signal to FM component power ratios.