Currently, Fuzzy Logic based algorithms are used identify radar data contaminated by AP clutter and then this data is censored so that precipitation estimates are not biased but this leaves data blanks. Radar operators can subsequently turn on clutter filters in those areas where there is AP clutter. This is tedious and prone to human error and is thus operationally impractical.
With the advent of fast digital radar receiver/processors, it is possible to identify clutter contaminated radar data and then apply a clutter filter to the contaminated data in real time. After the application of the clutter filter, radar moments are then calculated. In this way all clutter contaminated data is filtered but zero velocity weather data is retained for optimum data quality.
This paper describes a real time Fuzzy Logic algorithm for identifying and mitigating AP as well as NP clutter. New Fuzzy Logic membership function based on time series phase alignment, a power spectra parametr of the radar data as well as dual polarization moments are described. Data collected by the Denver NEXRAD KFTG and S-Pol, NCAR's (National Center for Atmospheric Research) polarimetric S-Band research radar, are used to illustrate the new algorithm termed Clutter Mitigation Decision (CMD).