A Novel Band-Stop Regression Filter with Application to Range-Velocity Mitigation for Weather Radar Data

Regression filters are typically used to either extract the trend of a signal (lowpass filter) or to estimate the high frequency content of a signal by subtracting the estimated trend from the original signal (highpass filter). However, it is possible to also use a regression least-square fit as a bandstop (or band pass) filter. The technique for doing this is described. The new regression bandstop filter offers distinct advantages over traditional FIR (finite impulse response), IIR (infinite impulse response) and spectral based filters, especially for shorter-length sequences, that can result in improved data quality. The advantages of the new regression bandstop filter are demonstrated via processing of SZ(8/64) phase coded data. SZ(8/64) is a technique used by NEXRAD (Next Generation Weather Radar) for extending the unambiguous velocity range. Specifically, the regression bandstop filter is used to suppress the strong-trip echo (i.e., most power) so that the velocity of the overlaid weak-trip echo can be estimated.