GNSS-MR用于雪深监测研究
发布时间：2018-08-06 10:28
【摘要】：GNSS测站周围的环境会对其观测值产生多路径效应影响,如何消除或削弱多路径效应一直受到广大学者的关注。与此相反,随着全球卫星导航系统研究与应用的不断深入,以GNSS-MR技术为代表的基于多路径效应影响的信噪比信息反演测站周围环境参数的课题成为一个新的研究热点,使得GNSS在地表遥感领域崭露头角。本文在国内外学者研究的基础上,从GNSS-MR技术基本原理出发,将其应用到雪深测量,并结合美国板块监测网络原始观测数据与SNOTEL雪深实测数据,重点对GNSS-MR用于雪深测量的可行性与精度进行研究分析。本文的主要研究内容和成果如下:1、对多路径效应与信噪比特征进行概述,讨论了多路径效应与信噪比之间的关系。低高度角信噪比数据受多路径效应影响较大,通过多项式拟合的方法可以实现直射信号与多路径反射信号的分离,进而利用多路径影响的信噪比信息实现地表环境参数的反演。2、对GNSS-MR技术的基本原理和计算流程进行阐述,对雪深探测范围与信号反射点轨迹进行讨论。GNSS-MR雪深探测范围大约是1000m2;GNSS信号反射点轨迹一方面可以实现GNSS-MR雪深监测的选星,一方面可以获取到积雪的空间分布信息。3、证明了信噪比残差序列的变化频率与降雪厚度成负相关关系。并从单颗卫星,多颗卫星,长时间序列3方面,层层递进,验证了GPS-MR雪深监测算法的可行性,其测量精度可以达到0.1m。4、对GPS-MR雪深测量技术精度影响因素进行分析,验证了合理的设置高度角范围,采用具有较高接收功率的信噪比数据以及高采样的数据都会对反演结果做出有益的贡献,其反演精度相对较高,反演结果也更加稳定。5、介绍了Rinex3.X格式的新变化,利用MATLAB语言设计GNSS-MR雪深测量数据处理系统,结合实测数据验证其正确性,并根据数据处理需求,输出相应的图表文档文件。当前,多频多模卫星导航系统发展迅猛,世界各地的GNSS跟踪站(如IGS,PBO,陆态网络等)也如雨后春笋般建成,GNSS-MR技术的研究具备得天独厚的资源与发展空间。随着研究与技术不断进步与成熟,GNSS-MR这种全新的遥感手段在实时地表环境监测(降雪、土壤湿度、海平面等)方面的应用让人期待!
[Abstract]:The environment around the GNSS station will have a multipath effect on its observation value. How to eliminate or weaken the multipath effect has been concerned by many scholars. On the contrary, with the development of the research and application of global satellite navigation system, the research on retrieving the environmental parameters around the station based on the signal to noise ratio (SNR) information based on multipath effect, represented by GNSS-MR technology, has become a new research hotspot. GNSS has made its mark in the field of remote sensing of the earth's surface. Based on the research of domestic and foreign scholars, this paper applies GNSS-MR technology to snow depth measurement, and combines the original observation data of American plate monitoring network and SNOTEL snow depth measurement data. The feasibility and accuracy of GNSS-MR for snow depth measurement are studied and analyzed. The main contents and results of this paper are as follows: 1. The characteristics of multipath effect and signal-to-noise ratio are summarized and the relationship between multipath effect and signal-to-noise ratio is discussed. The low altitude signal-to-noise ratio (SNR) data are greatly affected by multipath effect. The separation of direct and multipath reflected signals can be realized by polynomial fitting. Then using the signal-to-noise ratio (SNR) information of multipath influence to realize the inversion of surface environmental parameters, the basic principle and calculation flow of GNSS-MR technology are expounded. This paper discusses the range of snow depth detection and the track of signal reflection point. GNSS-MR snow depth detection range is about 1000m ~ (2) m ~ (2) GNSS-MR signal's reflection point trajectory. On the one hand, it can realize the selection of stars for GNSS-MR snow depth monitoring. On the one hand, the spatial distribution information of snow cover. 3 can be obtained, which proves that the variation frequency of SNR residuals is negatively related to the snowfall thickness. The feasibility of the GPS-MR snow depth monitoring algorithm is verified from three aspects of single satellite, multiple satellites and long time series. The accuracy of the algorithm can reach 0.1 m.4. the factors influencing the accuracy of GPS-MR snow depth measurement technology are analyzed. It is verified that setting the range of height angle reasonably, the SNR data with higher receiving power and the data with high sampling will all make beneficial contributions to the inversion results, and the inversion accuracy is relatively high. The inversion results are also more stable. 5. The new changes of Rinex3.X format are introduced. The GNSS-MR snow depth measurement data processing system is designed by using MATLAB language. The correctness of the system is verified by combining the measured data, and the corresponding chart document files are output according to the data processing requirements. At present, the multi-frequency and multi-mode satellite navigation system is developing rapidly, and the research of GNSS tracking stations (such as IGSS-PBO, land state network, etc.) all over the world has a unique resource and development space. With the development of research and technology, GNSS-MR, a new remote sensing tool, is expected to be used in real-time surface environment monitoring (snow, soil moisture, sea level, etc.).
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P228.4;P407
本文编号：2167446
[Abstract]:The environment around the GNSS station will have a multipath effect on its observation value. How to eliminate or weaken the multipath effect has been concerned by many scholars. On the contrary, with the development of the research and application of global satellite navigation system, the research on retrieving the environmental parameters around the station based on the signal to noise ratio (SNR) information based on multipath effect, represented by GNSS-MR technology, has become a new research hotspot. GNSS has made its mark in the field of remote sensing of the earth's surface. Based on the research of domestic and foreign scholars, this paper applies GNSS-MR technology to snow depth measurement, and combines the original observation data of American plate monitoring network and SNOTEL snow depth measurement data. The feasibility and accuracy of GNSS-MR for snow depth measurement are studied and analyzed. The main contents and results of this paper are as follows: 1. The characteristics of multipath effect and signal-to-noise ratio are summarized and the relationship between multipath effect and signal-to-noise ratio is discussed. The low altitude signal-to-noise ratio (SNR) data are greatly affected by multipath effect. The separation of direct and multipath reflected signals can be realized by polynomial fitting. Then using the signal-to-noise ratio (SNR) information of multipath influence to realize the inversion of surface environmental parameters, the basic principle and calculation flow of GNSS-MR technology are expounded. This paper discusses the range of snow depth detection and the track of signal reflection point. GNSS-MR snow depth detection range is about 1000m ~ (2) m ~ (2) GNSS-MR signal's reflection point trajectory. On the one hand, it can realize the selection of stars for GNSS-MR snow depth monitoring. On the one hand, the spatial distribution information of snow cover. 3 can be obtained, which proves that the variation frequency of SNR residuals is negatively related to the snowfall thickness. The feasibility of the GPS-MR snow depth monitoring algorithm is verified from three aspects of single satellite, multiple satellites and long time series. The accuracy of the algorithm can reach 0.1 m.4. the factors influencing the accuracy of GPS-MR snow depth measurement technology are analyzed. It is verified that setting the range of height angle reasonably, the SNR data with higher receiving power and the data with high sampling will all make beneficial contributions to the inversion results, and the inversion accuracy is relatively high. The inversion results are also more stable. 5. The new changes of Rinex3.X format are introduced. The GNSS-MR snow depth measurement data processing system is designed by using MATLAB language. The correctness of the system is verified by combining the measured data, and the corresponding chart document files are output according to the data processing requirements. At present, the multi-frequency and multi-mode satellite navigation system is developing rapidly, and the research of GNSS tracking stations (such as IGSS-PBO, land state network, etc.) all over the world has a unique resource and development space. With the development of research and technology, GNSS-MR, a new remote sensing tool, is expected to be used in real-time surface environment monitoring (snow, soil moisture, sea level, etc.).
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P228.4;P407
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