Ground clutter filtering for Weather radar using staggered pulse repetition time

In weather radar applications, Doppler processing techniques are used to determine parameters of interest from atmospheric phenomena, such as the average power of the signals that produce their reflections and their average speed. In the present work a technique of reconstruction of the digital spectrum was implemented from a set of data acquired at different sampling rates, which was used in conjunction with the adaptive processing algorithm based on the Gaussian model (GMAP) to determine the spectral moments of the reflections produced by atmospheric phenomena. Both methods were implemented and their joint performance was evaluated through numerical simulations. In particular, two different sampling rates were considered and as a measure of performance, the mean and the standard deviation of the estimated moments were used. The results show that the combination of these two algorithms present a performance comparable to that of GMAP with uniformly spaced samples.