Tuesday, 25 October 2005: 4:30 PM
Alvarado D (Hotel Albuquerque at Old Town)
Among the planned upgrades for the NEXRAD network of weather surveillance radars are super-resolution (1/4 km reflectivity and 0.5 deg radials) and polarimetric capabilities. In either case, keeping current update times (i.e., same antenna rotation rates) results in meteorological variable estimators with unacceptably large errors. A family of methods to reduce errors in estimates of spectral moments and polarimetric variables beyond those achievable with standard estimators has been proposed and is scheduled for inclusion in future upgrades of the WSR-88D Open Radar Data Acquisition (ORDA) subsystem. These techniques consist of oversampling echo signals in range, applying linear transformations to decorrelate the samples, processing the sequences in time at fixed range locations to obtain covariance estimates, averaging these covariances in range, and finally combining them to compute the variables. This paper demonstrates the enhanced performance of estimators based on oversampling and whitening techniques. Results on weather data collected with the NSSL's research WSR-88D confirm both simulations and analytical formulas. Compared to standard processing of signals using a matched filter, a reduction in variance by a factor equivalent to the number of samples within the pulse is achieved.
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