Removing Ground and Intermittent Clutter Contamination from Wind Profiler Signals Using Wavelet Transforms

Abstract New algorithms for removing ground and intermittent clutter contamination from wind profiler data are presented. The techniques use wavelet transforms to “filter” the contribution of clutter to the wind profiler signals. Examples of typical clutter contamination using simulated and actual signals are presented. The corresponding Doppler spectra before and after wavelet filtering are compared. The authors find that wavelet filtering can reduce the clutter-to-clear-air signal power by as much as 40 dB, even when the clutter and clear-air peaks cannot be resolved in the Doppler spectrum. The enhancement in clear-air signal detectability in the presence of clutter is due to the more efficient separation of clutter and clear-air energy in the wavelet domain.