Improved spectral resolution by energy-weighted prediction method

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Abstract
A new method of AR parameter estimation for maximum entropy spectral estimation is introduced using forward and backward optimal linear predictors weighted by the forward and backward process realization energies, respectively. AR parameters estimated by this Energy-Weighted (EW) method are constrained to satisfy the fast Levinson recursion. The reflection coefficients of each stage are computed from the harmonic mean of the same-stage energy weighted forward and backward reflection coefficients. AR spectra generated by the EW method are shown to have improved performance over AR spectra generated by the Burg algorithm. These improvements include sharper resolution, less frequency bias, less phase dependence, less noise spectral variance and absence of spectral line splitting. The EW method has the simplicity and the computational efficiency of the Burg Algorithm.