Application of Optimized Filters to Two-Dimensional Sidelobe Mitigation in Meteorological Radar Sensing

Two-dimensional reiterative minimum mean-square error and 2-D least-square solutions that mitigate the sidelobe effects of both pulse compression processing and antenna radiation patterns are derived and compared with traditional matched filtering. The methods are applied to observations of distributed weather targets. The results of simulations based on realistic weather model outputs and scattering models are presented, and sidelobe mitigation performance, based on average mean-square-error, is discussed.