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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:

第44卷

期数:

2022年第02期

页码:

352-362

栏目:

大地测量、遥感与地学大数据

出版日期:

2022-03-15

文章信息/Info

Title:

Method and Application of Identifying Multipath Errors in GNSS Observation Data Based on Prior Information of Base Station's Signal-to-noise Ratio

文章编号:

1672-6561(2022)02-0352-11

作者:

刘 健; 黄观文^*; 杜 源; 白正伟

(长安大学 地质工程与测绘学院,陕西 西安 710054)

Author(s):

LIU Jian;  HUANG Guan-wen^*;  DU Yuan;  BAI Zheng-wei

(School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China)

关键词:

全球卫星导航定位;  滑坡监测;  载波相位差分技术;  多路径效应;  基准站;  信噪比;  复杂环境;  数据剔除

Keywords:

GNSS;  landslide monitoring;  RTK;  multipath effect;  base station;  signal-to-noise ratio;  complex environment;  data elimination

分类号:

P228.1; P642.22

DOI:

10.19814/j.jese.2021.12035

文献标志码:

A

摘要:

在复杂监测环境下,全球卫星导航定位(GNSS)信号极易受环境干扰产生多路径误差,观测数据中包含大量较差的观测值,导致 GNSS监测精度降低甚至不可用。考虑到监测网中的基准站通常布设于开阔无遮挡环境,基准站和监测站跟踪的卫星信息相关性较强,提出一种基于基准站信噪比先验信息的GNSS观测数据多路径误差识别方法。该方法利用卫星信噪比观测值与多路径误差的强相关性,通过对信噪比观测值作站间差分来识别受多路径影响严重的较差数据,并对其进行剔除处理,以抵御复杂监测环境的多路径影响。以遮挡严重的河南三门峡地区某滑坡监测环境为例,基于实测数据验证表明,提出的新方法能够对受山体、植被、人工设施等多路径影响严重的较差观测值进行有效识别,环境自适应能力更强,显著提升了模糊度固定率及定位精度。提出的新方法模糊度固定率结果相比传统固定截止高度角(TFC)模型平均提高39.6%,相比自适应截止高度角(ADEM)模型平均提高28.6%; 固定解定位精度在E、N方向优于4 mm,U方向优于9 mm。

Abstract:

In a complex monitoring environment, GNSS signals, which are extremely susceptible to environmental interference, can produce multipath errors, and the observation data contain a large number of poor observation values, resulting in reduced GNSS monitoring accuracy or even unavailability. Considering that the base station in the monitoring network is usually deployed in an open and unobstructed environment, and the same satellite information tracked by the base station and the monitoring station has a strong correlation, the method of identifying multipath errors in GNSS observation data based on prior information of base station's signal-to-noise ratio(SNR)was proposed. This method utilizes the strong correlation between satellite SNR observations and multipath errors, identifies poor data seriously affected by multipath through making inter-station differences in SNR observations, and removes them to resist the multipath effects of complex monitoring environment. Taking the monitoring environment of one landslide with serious occlusion in Sanmenxia area of Henan as an example, the verification based on the measured data shows that the proposed method can effectively identify the poor observation values with serious multipath effect affected by mountains, vegetation and artificial facilities, has stronger environmental adaptability, and significantly improves the fixed rate of ambiguity and positioning accuracy. Compared with the traditional fixed cut-off(TFC)model and the azimuth-dependent elevation mask(ADEM)model, the proposed method's ambiguity fixed rates are improved by the average of 39.6% and 28.6%, respectively; the positioning accuracy of the fixed solution is better than 4 mm in the E and N directions, and better than 9 mm in the U direction.

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备注/Memo

备注/Memo:

收稿日期:2021-12-19; 修回日期:2022-02-25投稿网址:http:∥jese.chd.edu.cn/
基金项目:国家重点研发计划项目(2018YFC1505105); 国家自然科学基金项目(41941019,42090053)
作者简介:刘 健(1996-),男,陕西榆林人,工学硕士研究生,E-mail:19833399075@qq.com。
*通讯作者:黄观文(1983-),男,江苏淮安人,教授,博士研究生导师,工学博士,E-mail:guanwen@chd.edu.cn。

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更新日期/Last Update: 2022-04-30