Precipitation Spectral Moments Estimation and Clutter Mitigation using Parametric Time Domain Model

In this study the problem of precipitation signal spectral moments estimation in case of clutter contamination is considered. It is proposed to use a parametric model to estimate spectral moments of precipitation echoes and clutter. To estimate these spectral moments the maximum likelihood estimator based on the properties of Gaussian joint distribution of complex time series is used. The main advantage of this approach is that it does not suppress any part of the signal and the properties of weather echoes and clutter are estimated simultaneously. The performance of the proposed method is evaluated based on simulations of radar signals and compared to the performance of GMAP (Gaussian model adaptive processing). The proposed procedure is also applied to measurements collected by CSU- CHILL radar collected during summer 2004.