A spectral matching approach for parameter and spectral estimation of nonstationary rational processes

The parameter and spectral estimation problems of nonstationary signals are considered. The nonstationary signals are modeled as rational processes with time-varying parameters. The spectral matching approach, which was introduced by Friedlander and Porat (1984), is generalized to the nonstationary case and two new estimators, namely, the time-varying spectral matching estimator (TVSME) and the time-frequency spectral matching estimator (TFSME) are proposed. The proposed methods estimate the parameters of the time-varying rational model by fitting the parametric spectrum expression to an estimated time-frequency distribution of the signal. An approximate statistical analysis is given for both methods along with computer simulation results, illustrating the performance of the proposed estimators.