Analysis of the new NEXRAD spectrum width estimator

Recently, the US network of weather surveillance radars (NEXRAD) was upgraded with new receiver, signal processor, and control subsystems. Before this upgrade, the spectrum width was estimated using the standard pulse-pair technique. The new signal processor implements a similar spectrum width estimator, but relies on a DFT-based estimator to compute the first few lags of the time-series autocorrelation function. Initial evaluation of the upgraded system demonstrated that, if combined with a tapered data window, the DFT-based estimator produces results that are acceptable and very close to the classical pulse-pair estimator. However, this paper demonstrates that, in general, the new and legacy autocorrelation estimators are not equivalent, resulting in inconsistent spectrum width estimates. Theoretical, simulation, and data analyses show that the new spectrum width estimator on non-windowed data is positively biased, especially for narrow spectrum widths. Given that biased estimates would negatively impact the performance of algorithms that rely on the spectrum width (e.g., the radar echo classifier, or the new turbulence detection algorithm), we propose changes to the new spectrum width estimator to make it unbiased, mathematically equivalent to the pulse-pair implementation, and naturally able to handle data window effects.