Weather radar ground clutter. Part I: Identification, modeling, and simulation

Real-time ground-clutter identification and subsequent filtering of clutter-contaminated data is addressed in this two-part paper. Part I focuses on the identification, modeling, and simulation of S-band ground-clutter echo. A new clutter identification parameter, clutter phase alignment (CPA), is presented. CPA is a measure primarily of the phase variability of the in-phase and quadrature-phase time series samples for a given radar resolution volume. CPA is also a function of amplitude variability of the time series. It is shown that CPA is an excellent discriminator of ground clutter versus precipitation echoes. A typically used weather model, time series simulatoris shown to inadequately describe experimentally observed CPA. Thus, a new technique for the simulation of ground-clutter echo is developed that better predicts the experimentally observed CPA. Experimental data from the Denver Next Generation Weather Radar (NEXRAD) at the Denver, Colorado, Front Range Airport (KFTG), and NCAR’s S-band dual-polarization Doppler radar (S-Pol) are used to illustrate CPA. In Part II, CPA is used in a fuzzy logic algorithm for improved clutter identification.

[1]  H. Ward.  Radar reflectivity of land and sea , 1976, Proceedings of the IEEE.

[2]  V. Chandrasekar,et al.  A Parametric Time Domain Method for Spectral Moment Estimation and Clutter Mitigation for Weather Radars , 2008 .

[3]  Gregory Meymaris,et al.  Spectrum width estimators for the NEXRAD ORDA: Evaluation and recommendation [presentation] , 2007 .

[4]  Michael Dixon,et al.  Weather Radar Ground Clutter. Part II: Real-Time Identification and Filtering , 2009 .

[5]  Richard J. Doviak,et al.  Spectrum Width Measured by WSR-88D: Error Sources and Statistics of Various Weather Phenomena , 2004 .

[6]  J. B. Billingsley,et al.  Multifrequency Measurements of Radar Ground Clutter at 42 Sites. Volume 1. Principal Results , 1991 .

[7]  Matthias Steiner,et al.  Use of Three-Dimensional Reflectivity Structure for Automated Detection and Removal of Nonprecipitating Echoes in Radar Data , 2002 .

[8]  E. Jakeman,et al.  A model for non-Rayleigh sea echo , 1976 .

[9]  Robert R. Boothe,et al.  THE WEIBULL DISTRIBUTION APPLIED TO THE GROUND CLUTTER BACKSCATTER COEFFICIENT , 1969 .

[10]  Alfred J. Bogush.  Radar and the atmosphere , 1989 .

[11]  REGORY.  Spectrum Width Estimators for the NEXRAD ORDA: Evaluation and Recommendation , 2006 .

[12]  Rod Frehlich,et al.  Performance of Mean-Frequency Estimators for Doppler Radar and Lidar , 1994 .

[13]  M. Sekine,et al.  Weibull radar clutter , 1990 .

[14]  D. M. Green,et al.  Signal detection theory and psychophysics , 1966 .

[15]  J. Jao.  Amplitude distribution of composite terrain radar clutter and the κ-Distribution , 1984 .

[16]  J. Billingsley,et al.  Low-Angle Radar Land Clutter: Measurements and Empirical Models , 2002 .

[17]  K. M. Glover,et al.  Applications of radar to meteorological operations and research , 1974 .

[18]  Richard E. Passarelli,et al.  The Autocorrelation Function and Doppler Spectral Moments: Geometric and Asymptotic Interpretations , 1983 .

[19]  D. E. Kerr,et al.  Propagation of Short Radio Waves , 1989 .

[20]  D. Zrnic,et al.  Doppler Radar and Weather Observations , 1984 .

[21]  Peter T. M Ay,et al.  NOTES AND CORRESPONDENCE Reducing the Effect of Ground Clutter on Wind Profiler Velocity Measurements , 1998 .

[22]  R. Doviak,et al.  POLARIMETRIC DOPPLER WEATHER RADAR , 2022 .

[23]  M. R. Schaffner,et al.  Comments on "Applications of radar to meteorological operations and research" , 1975 .

[24]  K. A. Norton,et al.  The Probability Distribution of the Amplitude of a Constant Vector Plus a Rayleigh-Distributed Vector , 1955, Proceedings of the IRE.