Ground clutter recognition using polarimetric spectral parameters

The US National Weather Service is planning to upgrade the WSR-88D radar network with dual polarization. Thus significant new capability including recognition of echoes from ground clutter will become available. Thus far recognition of clutter was based on the values of polarimetric variables and no attempts were made on adaptively recognizing the clutter and filtering it from the signal. We describe an approach based on polarimetric spectral characteristics of dual polarization signals which allows adaptive clutter filtering. In essence the approach generates an “instantaneous clutter map”. Pairs of dual polarization signals from single range locations are subjected to polarimetric spectral analysis. Suitable combination of polarimetric spectral densities at and near zero velocity is used to identify presence or absence of clutter. In case of clutter presence the same spectral filter is applied to each component of the complex signal thus eliminating clutter. The remaining spectral coefficients are then used for computing the polarimetric variables. The method is independent of the spectral shape and is applicable to either “regular” clutter or clutter due to anomalous propagation. We apply this algorithm to polarimetric time series data obtained with NOAA/NSSL's radar, a modified version of the WSR-88D. Clutter recognition is compared to the data obtained from clutter maps. Thus probabilities of true recognition and the rates of false alarms for two types of filters applied in different situations are presented. Recommendations for possible implementation of the polarimetric spectral clutter suppression on the WSR-88D are discussed.