Intelligent mitigation of normal propagation and anomalous propagation clutter

Echoes from normal propagation ground clutter (NP) as well as anomalous propagation ground clutter (AP) contaminate weather echoes so that precipitation estimates based on such echoes are biased. One approach to alleviating this problem is to apply a ground clutter filter to all of the data. However, doing so has the potential to also eliminate zero velocity precipitation echoes.

Common fixed-width notch filters can be aggressive since they eliminate all power within a notch around a velocity of 0. The latest adaptive spectral-domain clutter filters represent an improvement because they are able to interpolate across the notch to restore the weather power removed by the notch. However, in regions of weather with a velocity close to zero and a narrow spectrum width, these filters will also remove weather power leading to biased moments and under-estimates of precipitation.

To solve this problem, the cutter-contaminated radar gates must be identified so that only those gates are filtered and gates with narrow-width, zero velocity weather are not filtered. Diagnostic fields such as the texture of the reflectivity, the stability of the clutter phase in the time domain, and the variability of dual polarization fields in range can provide this information. A fuzzy-logic algorithm combines these diagnostic fields into a clutter-likelihood field. The clutter filter is then applied only at those gates with a high likelihood of clutter.

This paper describes recent advances to the fuzzy logic algorithm for identifying and mitigating AP as well as NP clutter.