Instantaneous frequency estimation of non-stationary signals in a finitely correlated environment using a decorrelating time-varying autoregressive model

摘要

The performance of Time-Varying Autoregressive (TVAR) model have been shown well for Instantaneous Frequency (IF) estimation of frequency modulated (FM) components in white noise. Nevertheless the performance of the TVAR model degrades, when the model is applied to a signal containing a finitely correlated signal as well as the white noise, particularly when the correlated signal is not weak relative to the FM components. We modify the TVAR model by introducing a Decorrelation delay larger than one between the time-varying coefficients for IF estimation of non stationary signal in a finitely correlated environment. The resulting model is referred to as the Decorrelating TVAR (DTVAR) model. We showed the performance of Decorrelating TVAR (DTVAR) model based IF estimator is better than TVAR model based IF estimator in a finitely correlated environment. We also discussed the DTVAR Model order estimation using Maximum Likelihood Estimation (MLE) Algorithm. Simulation results are included to show the effectiveness of the modified method in a finitely correlated environment.