Polarimetric Spectral Filter for Adaptive Clutter and Noise Suppression

Abstract In this paper, spectral decompositions of differential reflectivity, differential phase, and copolar correlation coefficient are used to discriminate between weather and nonweather signals in the spectral domain. This approach gives a greater flexibility for discrimination between different types of scattering sources present in a radar observation volume. A spectral filter, which removes nonweather signals, is defined based on this method. The performance of this filter is demonstrated on the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) observations. It is shown that the resulting filter parameters are adaptively defined for each range sample and do not require an assumption on spectral properties of ground clutter.

[1]  H. L. Groginsky,et al.  Weather radar canceller design , 1980 .

[2]  T. Seliga,et al.  Statistical Properties of the Dual-Polarization Differential Reflectivity (ZDR) Radar Signal , 1983, IEEE Transactions on Geoscience and Remote Sensing.

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

[4]  M. Sachidananda,et al.  ZDR measurement considerations for a fast scan capability radar , 1985 .

[5]  M. Sachidananda,et al.  Efficient Processing of Alternately Polarized Radar Signals , 1989 .

[6]  Dino Giuli,et al.  Rainfall and Clutter Discrimination by Means of Dual-linear Polarization Radar Measurements , 1991 .

[7]  Petre Stoica,et al.  Introduction to spectral analysis , 1997 .

[8]  L. P. Ligthart,et al.  Doppler polarimetric ground clutter identification and suppression for atmospheric radars based on co-polar correlation , 2000, 13th International Conference on Microwaves, Radar and Wireless Communications. MIKON - 2000. Conference Proceedings (IEEE Cat. No.00EX428).

[9]  V. Chandrasekar,et al.  Classification of Hydrometeors Based on Polarimetric Radar Measurements: Development of Fuzzy Logic and Neuro-Fuzzy Systems, and In Situ Verification , 2000 .

[10]  V. Chandrasekar,et al.  Polarimetric Doppler Weather Radar: Principles and Applications , 2001 .

[11]  Reinaldo B. da Silveira,et al.  An automatic identification of clutter and anomalous propagation in polarization-diversity weather radar data using neural networks , 2001, IEEE Trans. Geosci. Remote. Sens..

[12]  Herman Russchenberg,et al.  A new method to separate ground clutter and atmospheric reflections in the case of similar Doppler velocities , 2002, IEEE Trans. Geosci. Remote. Sens..

[13]  A. D. Siggia,et al.  Gaussian model adaptive processing (GMAP) for improved ground clutter cancellation and moment calculation , 2004 .

[14]  Christine Unal,et al.  Combined Doppler and Polarimetric Radar Measurements: Correction for Spectrum Aliasing and Nonsimultaneous Polarimetric Measurements , 2004 .

[15]  V. Chandrasekar,et al.  Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[16]  H. Russchenberg,et al.  Retrieval of information about turbulence in rain by using Doppler-polarimetric Radar , 2005, IEEE Transactions on Microwave Theory and Techniques.

[17]  Marc Berenguer,et al.  A Fuzzy Logic Technique for Identifying Nonprecipitating Echoes in Radar Scans , 2006 .

[18]  Gyu Won Lee,et al.  Identification and Removal of Ground Echoes and Anomalous Propagation Using the Characteristics of Radar Echoes , 2006 .

[19]  Svetlana Bachmann,et al.  Spectral Density of Polarimetric Variables Separating Biological Scatterers in the VAD Display , 2007 .

[20]  Jonathan J. Gourley,et al.  A Fuzzy Logic Algorithm for the Separation of Precipitating from Nonprecipitating Echoes Using Polarimetric Radar Observations , 2007 .

[21]  V. Chandrasekar,et al.  Nonparametric Estimation of Raindrop Size Distributions from Dual-Polarization Radar Spectral Observations , 2007 .

[22]  V. Chandrasekar,et al.  Evaluation of first generation CASA radar waveforms in the IP1 testbed , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.