Extending the CLEAN-AP filter to staggered PRT signals in Doppler weather radars

The staggered pulse repetition time (PRT) algorithm has been shown to mitigate velocity and range ambiguities in Doppler weather radars by interlacing two sampling rates to decrease (or eliminate) velocity aliasing while maintaining adequate range coverage. However, the operational implementation of the staggered PRT algorithm still centers on providing adequate ground clutter filter suppression. Sachidananda and Zrnic (2000) proposed a solution to this issue by introducing the Spectral Algorithm for Clutter Harmonics Identification (SACHI) filter exploiting spectral processing using interlaced PRTs with a 2/3 ratio. In their approach, spectral analysis and clutter filtering are facilitated by the reconstruction of a uniformly sampled time sequence. Despite the effectiveness of this approach to filter ground clutter, it does not include the detection of ground clutter. Here, we present an alternative approach to spectral analysis and clutter mitigation (both detection and removal of ground clutter) for staggered PRT using autocorrelation spectral densities and the Clutter Environment Analysis using Adaptive Processing (CLEAN-AP) filter described by Warde and Torres (2009). Application and performance of this new algorithm is shown using simulations and recorded WSR-88D data. Comparisons to the SACHI filter are provided to gauge the filter performance of the new algorithm.