A parametric spectral moments estimation algorithm based on fitting autocorrelation sequence

The first three spectral moments of weather radar echoes are closely correlative with the types and characteristics of meteorological phenomena. The weather echoes and ground clutter have power spectra with shape following closely to Gaussian function. The first three spectral moments can be estimated using the modelled autocorrelation function. A parametric spectral moment estimator is proposed based on fitting the autocorrelation sequence. And the RELAX is used to deal with the scenarios of two or more mixed Gaussian spectrums. Finally, experimental results with simulated weather radar signals and performance analysis demonstrate that the present estimator is efficient with higher resolution.