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本文重点讨论根据（双偏振）天气雷达测量数据估计相差比Ｋｄｐ和线性去（偏振比ＬＤＲ本征值的信号处理技术。）从雷达测量的距离曲线提取有效数据段对参数的估计质量起着关键作用，尤其是对于由多个离散分布的小云团组成的暴雨结构，这更为重要。首先对原始数据的距离曲线进行适当的低通滤波，然后再对预处理过的数据应用自适应滤波。这个技术成功地应用于对风暴结构的精确分析和对降雨量的准确估计。
This article focuses on estimating the phase difference ratio (Kdp) and linearity (polarization ratio LDR eigenvalue signal processing techniques) based on (dual-polarization) weather radar measurement data. Extracting valid data segments from radar distance curves plays a key role in estimating the quality of parameters. This is especially important for heavy rain structures consisting of multiple, discretely distributed, small clouds. First, the low-pass filtering of the original data’s distance curve is performed, and then adaptive filtering is applied to the preprocessed data. This technique has been successfully applied to the accurate analysis of storm structures and the accurate estimation of rainfall.