Editorial Type:
Article
Article Type:
Research Article

Multilag Correlation Estimators for Polarimetric Radar Measurements in the Presence of Noise

Lei Lei * School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Guifu Zhang * School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma
School of Meteorology, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Richard J. Doviak NOAA/National Severe Storms Laboratory, Norman, Oklahoma
* School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma
School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Robert Palmer * School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma
School of Meteorology, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Boon Leng Cheong Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Ming Xue School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Qing Cao Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Yinguang Li * School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, University of Oklahoma, Norman, Oklahoma

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Print Publication:
01 Jun 2012
DOI:
https://doi.org/10.1175/JTECH-D-11-00010.1
Page(s):
772–795
Restricted access

Abstract

The quality of polarimetric radar data degrades as the signal-to-noise ratio (SNR) decreases. This substantially limits the usage of collected polarimetric radar data to high SNR regions. To improve data quality at low SNRs, multilag correlation estimators are introduced. The performance of the multilag estimators for spectral moments and polarimetric parameters is examined through a theoretical analysis and by the use of simulated data. The biases and standard deviations of the estimates are calculated and compared with those estimates obtained using the conventional method.

Corresponding author address: Guifu Zhang, Suite 5900, 120 David L. Boren Blvd., School of Meteorology, University of Oklahoma, Norman, OK 73072. E-mail: guzhang1@ou.edu

Abstract

The quality of polarimetric radar data degrades as the signal-to-noise ratio (SNR) decreases. This substantially limits the usage of collected polarimetric radar data to high SNR regions. To improve data quality at low SNRs, multilag correlation estimators are introduced. The performance of the multilag estimators for spectral moments and polarimetric parameters is examined through a theoretical analysis and by the use of simulated data. The biases and standard deviations of the estimates are calculated and compared with those estimates obtained using the conventional method.

Corresponding author address: Guifu Zhang, Suite 5900, 120 David L. Boren Blvd., School of Meteorology, University of Oklahoma, Norman, OK 73072. E-mail: guzhang1@ou.edu
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Journal of Atmospheric and Oceanic Technology

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