首页> 外文会议>30th International Conference on Radar Meteorology, Jul 19-24, 2001, Munich, Germany >ESTIMATION OF POLARIZATION ERRORS FROM COVARIANCE MATRICES OF CSU-CHILL RADAR DATA
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ESTIMATION OF POLARIZATION ERRORS FROM COVARIANCE MATRICES OF CSU-CHILL RADAR DATA

机译:从CSU-Chill雷达数据的协方差矩阵估计极化误差

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The covariance matrix of weather targets can be measured by the CSU-CHILL radar which alternately transmits pulses of H (horizontal) and V (vertical) polarized energy and receives simultaneously both H and V polarized signals. The covariance matrix is a function of not only the scattering process but is also contaminated by polarization errors of the radar. If the covariance matrices are well calibrated it is possible to estimate these polarization errors from data. The expected value of the polarization errors is quite small and thus the copolar measurends will be negligibly affected. However, the crosspolar measurands can be greatly affected even by polarization errors of a few tenths of a degree (Hubbert et al., 1999). Thus knowledge of polarization errors is important to the interpretation of radar variables such as LDR (liner depolarization ratio) and ρ_(hh,vh), the co-to-cross correlation coefficient.
机译:气象目标的协方差矩阵可以通过CSU-CHILL雷达测量,该雷达交替发送H(水平)和V(垂直)极化能量的脉冲,并同时接收H和V极化信号。协方差矩阵不仅是散射过程的函数,而且还受到雷达极化误差的污染。如果协方差矩阵得到了很好的校准,则可以从数据中估计出这些偏振误差。极化误差的期望值非常小,因此对同极测量数的影响可以忽略不计。然而,即使极化误差只有十分之几度,交叉极化被测物也会受到很大影响(Hubbert等,1999)。因此,极化误差的知识对于解释雷达变量(例如,LDR(线性去极化比率)和ρ_(hh,vh),即跨相关系数)很重要。

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