High-resolution instantaneous frequency estimation based on time-varying AR modeling

Time-varying autoregressive (TVAR) modeling based instantaneous frequency (IF) estimation has been considered a poor estimator since being proposed in 1984. As a result, not much further investigation of this method was reported in the literature. We present our recent work on this method, which leads us to conclude that, contrary to the prevailing opinion, the TVAR based IF estimation performs well, and is especially suitable for those practical cases where only a short data record is available and linear IF law can not be assumed. TVAR model based IF estimation is thus worthy of further research. We compare TVAR based IF estimation with the Wigner-Ville distribution (WVD) peak based method, which reveals performance ceilings due to end-effects, frequency quantization error, and bias associated with the WVD based approach.