Abstract: Systems and methods that adapt to the weather and clutter in a weather radar signal and apply a frequency domain approach that uses a Gaussian clutter model to remove ground clutter over a variable number of spectral components that is dependent on the assumed clutter width, signal power, Nyquist interval and number of samples. A Gaussian weather model is used to iteratively interpolate over the components that have been removed, if any, thus restoring any overlapped weather spectrum with minimal bias caused by the clutter filter. The system uses a DFT approach. In one embodiment, the process is first performed with a Hamming window and then, based on the outcome, the Hamming results are kept or a portion of the process is repeated with a different window. Thus, proper windows are utilized to minimize the negative impact of more aggressive windows.

Abstract: A system and method for processing data related to weather phenomena in a meteorological radar system. The method includes receiving an echo signal generated by transmitting a long pulse and employing a mismatched windowed filter on the echo signal such that the echo signal is compressed in time to achieve fine range resolution without substantially degrading sensitivity and while achieving low range time side lobes for Doppler velocities expected to be measured by the meteorological radar system.