基于GNSS极化掩星信号的降水观测数据周跳处理算法分析

Analysis of cycle slip processing algorithm for precipitation observation data based on GNSS polarimetric occultation signal

利用全球卫星导航系统(GNSS)极化掩星信号提取降水信息是国际上新兴起的研究领域.针对在前期理论研究、仿真分析和地基试验的基础上,重点解决地基试验数据中的周跳处理问题.结合地基试验双极化载波相位数据的特点,系统对比分析了高次差法、多普勒观测值法等6种常用周跳处理算法的可行性和适用范围,进而研究对高次差法进行改进以解决人为确定求差次数问题,最后通过仿真分析及实测数据验证了该方法的可靠性和有效性.结果表明:该方法能够准确探测出无雨和有雨时水平极化载波相位和垂直极化载波相位的各类大小周跳,可有效应用于GNSS极化掩星信号的降水观测数据处理.

Extracting precipitation information by Global Navigation Satellite System(GNSS)polarimetric occultation signal is a new research field in the world. Based on the previous theoretical research, simulation analysis and ground-based experiments, this paper focuses on solving the problem of cycle slip in the data of ground-based experiments. Combined with the characteristics of carrier phase data of ground-based experiments, the feasibility and application scope of six commonly used cycle slip detection algorithms, such as high-order difference method and doppler observation value method, are systematically compared and analyzed, and then the high-order difference method is improved to solve the problem of manually determining the number of times of difference. Finally, the reliability and effectiveness of this method are verified through simulation analysis and measured data. The results show that this method can accurately detect all kinds of cycle slips of horizontally polarized carrier phase and vertically polarized carrier phase under rain free and rainy conditions, and can be effectively applied to the precipitation observation data processing of GNSS polarimetric occultation signal.