Analysis of Sensitive Parameters of 15～23 GHz Microwave Link Induced by Rain Attenuation
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摘要: 为了提高微波链路雨衰特征的描述精度，拓展微波链路信号的可用参数，该文利用部署于江苏江阴地区的15 GHz, 18 GHz和23 GHz微波链路和雨量计开展同步对比观测，拟合得到3种频段的微波链路雨衰关系。提取并分析了接收信号电平的平均值、中位数、25%分位数、75%分位数、标准差、极大值和极小值等13个特征量与晴雨时刻、降雨强度之间的关系，得出结论：微波链路的信号变化和降雨强度的变化存在明显的负相关关系。实际拟合的雨衰关系与ITU-R的经验雨衰关系具有较好的一致性，但是在不同频段上均有差异；所有13个参量在有雨时刻和无雨时刻均存在一定概率的重叠，这是造成晴雨区分困难的主要原因；频率越高，信号变化受降雨的影响越显著，越有利于微波链路反演降雨。所得出的结论为提高微波链路测雨方法中的晴雨区分、参考值确定以及雨强反演的精度提供重要依据。Abstract: To improve the description accuracy of the characteristics of microwave link induced by rain attenuation and expand the available parameters of microwave link signals, the 15 GHz, 18 GHz and 23 GHz microwave links and rain gauges deployed in Jiangyin area of Jiangsu Province are used to carry out synchronous comparative observation, and the rain attenuation relationship at three frequency bands are fitted. The relationship between the 13 features of the received signal level (including the average, median, 25% quantile, 75% quantile, standard deviation, maximum, minimum, etc.) and the rain/no-rain period and rainfall intensity is extracted and analyzed. The conclusions are as follows. There is an obvious negative correlation between the signal of microwave link and the rainfall intensity. There is a general good consistency between the fitted rain attenuation relationship and the ITU-R empirical rain attenuation relationship, but there are certain of differences in different frequencies; All 13 parameters have a certain probability of overlap in the rain period and no-rain period, which is the main reason why it is difficult to distinguish between rain and no-rain; The higher is the frequency, the more significant is the impact of rainfall on the signal change, the more conducive to the microwave link inversion of rainfall. The results provide an important basis for improving the discrimination of rain and no-rain, and determination of reference value and inversion of rain intensity.
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Key words:
- Microwave link /
- Rainfall /
- Rain attenuation relationship /
- Features
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表 1 微波信号特征量
序号 特征量 公式 序号 特征量 公式 1 中位数 ${m_{0.5}} = {X_{(N + 1)/2}}$ 7 方差 ${S^2} = \dfrac{1}{N}\displaystyle\sum\limits_{i = 1}^N {{{({X_i} - \bar X)}^2}} $ 2 25%分位数 ${m_{0.25}} = {X_{(N + 1)/2}}$ 8 标准差 $\sigma = \sqrt {\dfrac{1}{N}\displaystyle\sum\limits_{i = 1}^N {{{({X_i} - \bar X)}^2}} } $ 3 75%分位数 ${m_{0.75}} = {X_{(N + 1)/2}}$ 9 斜率 $Sl = \dfrac{{\left( {\displaystyle\sum {t_i^2} } \right)\left( {\displaystyle\sum {{X_i}} } \right) - \left( {\displaystyle\sum {{t_i}} } \right)\left( {\displaystyle\sum {{t_i}{X_i}} } \right)}}{{N\left( {\displaystyle\sum {t_i^2} } \right) - {{\left( {\displaystyle\sum {{t_i}} } \right)}^2}}}$ 4 极大值 ${X_{\max } } = \max ({X_1}\; {X_2}\; ··· \;{X_N})$ 10 偏度 $Sk = \dfrac{{\dfrac{1}{N}\displaystyle\sum\limits_{i = 1}^N {{{({X_i} - \bar X)}^3}} }}{{{{\left( {\dfrac{1}{N}\displaystyle\sum\limits_{i = 1}^N {{{({X_i} - \bar X)}^2}} } \right)}^{\dfrac{3}{2}}}}}$ 5 极小值 ${X_{\min } } = \min ({X_1}\; {X_2} \;··· \; {X_N})$ 11 峰度 $Ku = \dfrac{{\dfrac{1}{N}\displaystyle\sum\limits_{i = 1}^N {{{({X_i} - \bar X)}^4}} }}{{{{\left( {\dfrac{1}{N}\displaystyle\sum\limits_{i = 1}^N {{{({X_i} - \bar X)}^2}} } \right)}^2}}}$ 6 众数 ${X_{mo}} = L + \dfrac{{{f_b}}}{{{f_a} + {f_b}}} \cdot i$ 12 信息熵 $HU = - \displaystyle\sum\limits_{i = 1}^N {P({X_i}){{\log }_2}P({X_i})} $ 
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表 2 微波链路信号特征量与雨强的相关系数
序号 特征量 与雨强的相关系数(%) 15 GHz 18 GHz 23 GHz 1 平均值 –42.84 –69.52 –82.36 2 中位数 –41.83 –70.58 –81.58 3 25%分位数 –44.24 –70.14 –81.52 4 75%分位数 –38.38 –60.76 –77.61 5 极大值 –34.52 –52.82 –75.38 6 极小值 –46.37 –70.48 –77.50 7 众数 –44.35 –70.78 –77.08 8 方差 31.58 46.66 27.40 9 标准差 39.88 58.46 43.86 10 斜率 12.68 41.41 10.62 11 偏度 2.99 3.35 8.37 12 峰度 5.52 0.66 0.75 13 信息熵 9.14 3.43 4.23
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