基于GNSS信号极化相移的区域降雨强度反演技术研究

With the rapid development of the Global Navigation Satellite System (GNSS), the GNSS remote sensing technology of atmospheric and oceanic environment, which aims to fully tap the value of GNSS big data, has attracted extensive attention, and some technologies have been implemented in business applications. In recent years, there has been a preliminary research on the perception of rainfall information based on GNSS polarization signals internationally, and of course there are a series of key technology and scientific problems to be solved. On the basis of forward modeling, inversion algorithm and foundation experiment, this project focuses on solving the problem of regional rain information acquisition, and carries out the technology research of retrieving regional rain rate based on polarimetric phase shift of GNSS signals. Firstly, the mathematical relation between specific differential phase shift of GNSS signals and rain rate is explored based on the calculated results of specific differential phase shift of L-band GNSS signals. Secondly, based on the CT technique, a mathematical and physical model for inversion of specific differential phase shift using polarimetric phase shift of GNSS signals is established, and a specific tomographic inversion algorithm is proposed. This research will lay the foundation for achieving a wide range or even global observation of rainfall, and provide technical support for China's independent development of remote sensing system for rain rate based on GPS and Beidou GNSS signals.

随着全球导航卫星系统GNSS的蓬勃发展，充分挖掘GNSS大数据价值的GNSS大气海洋遥感技术得到了广泛关注，部分技术已实现业务化应用。近年来，国际上兴起了基于GNSS极化信号感知降雨信息的初步研究，当然也存在一系列关键技术和科学问题需要解决。本项目在前期正演模型、反演算法和地基实验的基础上，着重解决区域降雨信息的获取问题，开展基于GNSS信号极化相移反演区域降雨强度的技术研究。首先，结合L波段GNSS信号差分传播相移常数的计算结果，探索研究GNSS信号差分传播相移常数与降雨强度之间的数学关系；其次，借鉴CT技术，建立利用GNSS信号极化相移反演差分传播相移常数分布的数学物理模型，并提出针对性的层析反演算法，从而为实现对降雨的大范围、甚至全球观测奠定基础，为我国自主发展基于GPS和北斗等GNSS信号的降雨强度遥测系统提供技术支撑。

充分挖掘全球导航卫星系统GNSS信号资源的大气海洋遥感技术一直是一个研究热点。本项目紧跟GNSS信号极化特征获取降水信息这一国际上新兴起的研究思路，持续开展相关研究，重点解决雨区路径长度与降雨强度之间的模糊问题和区域降水信息获取问题，开展GNSS信号极化相移获取区域降雨强度相关技术研究。在GNSS信号入射到单一降雨粒子散射特征分析的基础上，结合自然界中雨滴谱分布特征，构建了差分传播相移常数与降雨强度的数据集，进而通过求解二者经验关系模型参数，得出了差分传播相移常数与降雨强度的数学关系模型。以GNSS-LEO掩星事件为背景，基于GNSS掩星信号经过雨团产生极化相移的物理特性，借鉴计算机层析技术的原理，构建了层析雨团垂直结构的数学物理模型，并提出了采用两种反演算法（TSVD法、Tikhonov法）及两种正则化参数选取方法（L曲线准则、GCV准则）的反演方案；通过数值模拟，分别研究了该方案在超定和欠定情况下的可行性，并对比分析了不同反演算法的效果。结果表明：超定情况时，上述算法均能较准确地重构出雨团垂直结构，和原始分布的相关系数超过0.96，且不同算法采用不同正则化参数选取方法时结果相同；欠定条件下，甚至在未知数个数远大于观测量个数时，该方案仍可重构出雨团信息，不同仿真试验最优结果的相关系数位于0.75—0.98之间，且Tikhonov法明显优于TSVD法。这些研究对利用GNSS信号获取区域雨团信息进行了有益探索，为后续低轨卫星载荷方案设计和论证提供了技术支撑。

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