Weather Radar Spectral Estimation Using Sparse Models

In weather radar systems, the echoes from the weather phenomena can be contaminated by ground reflections (clutter). If this interference is not properly removed, it produces biased estimates of the meteorological variables, or it can even hide the signal of interest. In this paper, we analyze different formulations of sparse models for estimating the Doppler spectrum and spectral moments of the radar signal. The performance of the sparse models is compared with classical ground clutter filters using synthetic data; and then validated using real data provided by INVAP through their weather radar located in Bariloche.