Non-stationary Signal Analysis using TVAR Model

Abstract

In this paper Time-varying Auto regressive model (TVAR) based approach for instantaneous frequency(IF) estimation of the frequency modulated signal in noisy environment is presented. Covariance method is applied for least square estimation of timevarying autoregressive parameters. Time-varying parameters are expressed as a linear combination of constants multiplied by basis functions. Then, the time-varying frequencies are extracted from the time-varying parameters by calculating the angles of the estimation error filter polynomial roots. The experimental results are presented for IF estimation, prediction and power spectrum estimation of non stationary signals. we have also discussed the spectral resolution ability of TVAR Model. Simulation and experimental results demonstrate that TVAR is an effective solution to non-stationary signal analysis and has strong capability in signal time-frequency feature extraction.