Estimation of transmitted differential phase on dual polarization radars

IF 1.9 4区 地球科学 Q2 ENGINEERING, OCEAN
D. Zrnić, V. Melnikov
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引用次数: 0

Abstract

A measurement procedure to determine transmitted differential phase between horizontally and vertically polarized radiation of a dual polarization radar is presented. It is applicable to radars that transmit and receive Simultaneously Horizontally and Vertically (SHV) polarized waves. The method relies solely on weather data with no instrument intrusions whatsoever. It takes data at vertical incidence while the antenna rotates in azimuth. That way a large number of samples is collected to reduce statistical errors in estimates. The theory indicates that the transmitted differential phase appears prominently in the backscatter signals off the melting layer. That and relations between various elements of the backscattering matrix are used to derive a set of nonlinear equations whereby the differential phase on transmission is one of the unknowns. Steps for solving these equations are presented as well as a demonstration of the results on radar data. Finally, a simplified algorithm that bypasses the coupled nonlinear equations is exposed. Conditions under which the simplification can be applied are presented. These restrict the range of the transmitted differential phase for which the simplified procedure may be applied.
双偏振雷达上传输差相位的估计
提出了一种确定双极化雷达水平和垂直极化辐射之间传输差相位的测量方法。它适用于同时发射和接收水平和垂直(SHV)极化波的雷达。该方法完全依赖于天气数据,没有任何仪器入侵。当天线在方位角上旋转时,它以垂直入射角获取数据。这样可以收集大量样本,以减少估计中的统计误差。该理论表明,透射微分相位在熔化层外的反向散射信号中表现突出。这一点以及后向散射矩阵的各个元素之间的关系被用来导出一组非线性方程,其中传输时的微分相位是未知数之一。给出了求解这些方程的步骤,并对雷达数据的结果进行了演示。最后,给出了一种绕过耦合非线性方程组的简化算法。给出了可以应用简化的条件。这些限制了可以应用简化过程的传输差分相位的范围。
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来源期刊
CiteScore
4.50
自引率
9.10%
发文量
135
审稿时长
3 months
期刊介绍: The Journal of Atmospheric and Oceanic Technology (JTECH) publishes research describing instrumentation and methods used in atmospheric and oceanic research, including remote sensing instruments; measurements, validation, and data analysis techniques from satellites, aircraft, balloons, and surface-based platforms; in situ instruments, measurements, and methods for data acquisition, analysis, and interpretation and assimilation in numerical models; and information systems and algorithms.
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