Whitening in Range to Improve Weather Radar Spectral Moment Estimates. Part II: Experimental Evaluation

Ivić, Igor R.; Zrnić, Dúsan S.; Torres, Sebastián

doi:10.1175/1520-0426(2003)020<1449:wirtiw>2.0.co;2

Cited by 18 publications

(6 citation statements)

References 7 publications

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“…It is shown that oversampling range samples using a wideband receiver and subsequently whitening the range samples would provide estimates with minimum error for any spectral moments in agreement with the results of Ivic et al (2003). It is shown that oversampling range samples using a wideband receiver and subsequently whitening the range samples would provide estimates with minimum error for any spectral moments in agreement with the results of Ivic et al (2003).…”

Section: Discussionsupporting

confidence: 63%

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Wideband Reception and Processing for Dual-Polarization Radars with Dual Transmitters

Choudhury

Chandrasekar

2007

Journal of Atmospheric and Oceanic Technology

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Oversampling pulsed Doppler radar returns at a rate larger than the pulse bandwidth, whitening the range samples, and subsequent averaging has been pursued as a potential way to decrease the measured standard deviation of signal parameter estimates. It has been shown that the application of oversampling, whitening, and subsequent averaging improves the quality of reflectivity, mean velocity, and spectral width estimates in agreement with theory. Application of this procedure to a dual-polarization radar with dual transmitters is evaluated in this paper. Oversampled data collected from the Colorado State University (CSU)-University of Chicago-Illinois State Water Survey (CHILL) radar using a wideband receiver are analyzed to evaluate the performance of dual-polarization parameter estimators, such as differential reflectivity and differential phase. The negative impact of relative phase characteristics of the transmitted pulses in two polarizations on the copolar correlation, and subsequently on polarimetric parameter estimation, is analyzed. CSU-CHILL radar's transmitted pulse sampling capability is used to evaluate the impact of the transmitted waveform's mismatch on whitening and estimation.

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Section: Discussionsupporting

confidence: 63%

“…Computation of the transformation matrix from a real correlation matrix has also been suggested by Ivic et al (2003). The whitening transformation matrix is computed by using the magnitude of the correlation functions.…”

Section: January 2007 C H O U D H U R Y a N D C H A N D R A S E K A Rmentioning

confidence: 99%

Wideband Reception and Processing for Dual-Polarization Radars with Dual Transmitters

Choudhury

Chandrasekar

2007

Journal of Atmospheric and Oceanic Technology

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“…Full utilization of fine-resolution data would require a technique for reducing the variance of the parameter estimates. One promising technique is the range oversampling and whitening approach proposed by Torres and Zrnić (2003) and evaluated by Ivić et al (2003). The technique works by oversampling in range-that is, by acquiring many samples within a range cell, and then manipulating these samples such that they become decorrelated.…”

Section: Concluding Discussionmentioning

confidence: 99%

Improved Detection of Severe Storms Using Experimental Fine-Resolution WSR-88D Measurements

Brown

Flickinger

Forren

et al. 2005

Weather and Forecasting

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Doppler velocity and reflectivity measurements from Weather Surveillance Radar-1988 Doppler (WSR-88D) radars provide important input to forecasters as they prepare to issue short-term severe storm and tornado warnings. Current-resolution data collected by the radars have an azimuthal spacing of 1.0°and range spacing of 1.0 km for reflectivity and 0.25 km for Doppler velocity and spectrum width. To test the feasibility of improving data resolution, National Severe Storms Laboratory's test bed WSR-88D (KOUN) collected data in severe thunderstorms using 0.5°-azimuthal spacing and 0.25-km-range spacing, resulting in eight times the resolution for reflectivity and twice the resolution for Doppler velocity and spectrum width. Displays of current-resolution WSR-88D Doppler velocity and reflectivity signatures in severe storms were compared with displays showing finer-resolution signatures. At all ranges, fine-resolution data provided better depiction of severe storm characteristics. Eighty-five percent of mean rotational velocities derived from fine-resolution mesocyclone signatures were stronger than velocities derived from current-resolution signatures. Likewise, about 85% of Doppler velocity differences across tornado and tornadic vortex signatures were stronger than values derived from current-resolution data. In addition, low-altitude boundaries were more readily detected using fine-resolution reflectivity data. At ranges greater than 100 km, fineresolution reflectivity displays revealed severe storm signatures, such as bounded weak echo regions and hook echoes, which were not readily apparent on current-resolution displays. Thus, the primary advantage of fine-resolution measurements over current-resolution measurements is the ability to detect stronger reflectivity and Doppler velocity signatures at greater ranges from a WSR-88D.

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“…Figure 1 shows the normalized standard errors of WTB, MFB, and OAB (a) differential reflectivity, (b) differential phase, and (c) cross-correlation coefficient estimators as a function of the SNR for the ideal case, a normalized spectrum width of 0.08, and true Z DR of 1 dB and HV of 0.98, which are representative of pure rain (Straka et al 2000). The oversampling factor L ϭ 8 is a realistic value that can be achieved on weather surveillance radar (Ivic et al 2003). When compared to MFB (or OAB) estimates, WTB estimates exhibit a superior performance for large SNR.…”

Section: Magnitude Of Zero-lag Cross-correlation Coefficient Estimmentioning

confidence: 99%

Whitening of Signals in Range to Improve Estimates of Polarimetric Variables

Torres

Zrnić

2003

J. Atmos. Oceanic Technol.

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A method to reduce errors in estimates of polarimetric variables beyond those achievable with standard estimators is suggested. It consists of oversampling echo signals in range, applying linear transformations to decorrelate these samples, processing in time the sequences at fixed range locations to obtain various secondorder moments, averaging in range these moments, and, finally, combining them into polarimetric variables. The polarimetric variables considered are differential reflectivity, differential phase, and the copolar correlation coefficient between the horizontally and vertically polarized echoes. Simulations and analytical formulas confirm a reduction in variance proportional to the number of samples within the pulse compared to standard processing of signals behind a matched filter. This reduction is possible, however, if the signal-to-noise ratios (SNRs) are larger than a critical value. Plots of the critical SNRs for various estimates as functions of Doppler spectrum width and other parameters are provided.

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Whitening in Range to Improve Weather Radar Spectral Moment Estimates. Part II: Experimental Evaluation

Cited by 18 publications

References 7 publications

Wideband Reception and Processing for Dual-Polarization Radars with Dual Transmitters

Wideband Reception and Processing for Dual-Polarization Radars with Dual Transmitters

Improved Detection of Severe Storms Using Experimental Fine-Resolution WSR-88D Measurements

Whitening of Signals in Range to Improve Estimates of Polarimetric Variables

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