A time domain clutter filter for staggered PRT and dual- PRF measurements

In this paper, a method for clutter filtering and the estimation of spectral moments from non-uniformly sampled Doppler weather radar signals is presented. The method uses a parametric model for the received signal. The spectral moments of both clutter and precipitation echoes are estimated using the maximum likelihood estimator. Unlike the current frequency domain techniques where non-uniformly sampled signals are zero-padded to be uniform sequences, the likelihood function used in this algorithm can be constructed directly from the non- uniformly sampled data. Therefore an accurate estimation of spectral moments even in case of clutter - to - signal ratio as high as 60 dB can be obtained. The proposed method is illustrated on simulated radar signal time series and measurements collected using the staggered pulse repetition time (PRT) and dual pulse repetition frequency (PRF) transmission schemes from the CSU- CHILL and collaborative adaptive sensing of atmosphere (CASA) IP1 radars.