Clutter Filtering and Spectral Moment Estimation for Doppler Weather Radars Using Staggered Pulse Repetition Time (PRT)

Abstract

In this paper, a new algorithm for the estimation of spectral parameters from the signal time series, collected using the staggered pulse repetition time (PRT) transmission in a Doppler weather radar, is presented. The algorithm uses the Fourier transform and a magnitude deconvolution procedure to reconstruct the signal spectrum, and then the spectral parameters are estimated from the reconstructed spectrum. There is a significant improvement in the variance of the spectral parameter estimates compared to previously published methods of processing staggered PRT sequences. Further, a novel spectral domain clutter filtering procedure allows 1) accurate velocity estimation even if the clutter-to-signal power ratio is as high as 40 dB and 2) does not incur the loss of velocity information in certain Doppler bands experienced by other clutter filtering techniques. With this algorithm, the staggered PRT technique becomes a practical contender for implementation on Doppler weather radars in the quest to increase the unambiguous velocity and range.