The Use of Coherency to Improve Signal Detection in Dual-Polarization Weather Radars

Abstract

Abstract Currently, signal detection and censoring in operational weather radars is performed by using thresholds of the estimated signal-to-noise ratio (SNR) and/or the magnitude of the autocorrelation coefficient at the first temporal lag. The growing popularity of polarimetric radars prompts the quest for improved detection schemes that take advantage of the signals from the two orthogonally polarized electric fields. A hybrid approach is developed based on the sum of the cross-correlation estimates as well as the powers and autocorrelations from each of the dual-polarization returns. The hypothesis that “signal is present” is accepted if the sum exceeds a predetermined threshold; otherwise, the data are considered to represent noise and are censored. The threshold is determined by the acceptable rate of false detections that is less than or equal to a preset value. The scheme is evaluated both in simulations and through implementation on time series data collected by the research weather surveillance radar (KOUN) in Norman, Oklahoma.