Echo classification within the spectral domain to discriminate ground clutter from meteorological targets

Clutter filters tend to remove meteorological signals in situations in which the spectral signature of the weather (especially stratiform precipitation) resembles that of ground clutter. To better discriminate between weather and ground clutter additional information is required. Promising sources of such information are (a) the nature of the reflectivity pattern around the clutter target, (b) the variance of the velocity, (c) spectral characteristics, and (d) the variance of dual polarization variables. We present a radar echo classification scheme based on a fuzzy combination of these variables. We apply this scheme to several cases and demonstrate that it is effective in discriminating between ground clutter and weather echoes. This classification scheme is suitable for real-time radar applications and can be used as a decision support system to control the application of the clutter filters only to clutter targets and not to weather echoes. Better preservation of the reflectivity values within stratiform precipitation that is near the zero m/s radial velocity contour is achieved.