舒宝, 何元浩, 王利, 周星, 张勤, 黄观文. 一种适用于大尺度卫星导航定位基准站的网络RTK方法[J]. 武汉大学学报 ( 信息科学版), 2021, 46(11): 1609-1619. DOI: 10.13203/j.whugis20210202
引用本文: 舒宝, 何元浩, 王利, 周星, 张勤, 黄观文. 一种适用于大尺度卫星导航定位基准站的网络RTK方法[J]. 武汉大学学报 ( 信息科学版), 2021, 46(11): 1609-1619. DOI: 10.13203/j.whugis20210202
SHU Bao, HE Yuanhao, WANG Li, ZHOU Xing, ZHANG Qin, HUANG Guanwen. A Network RTK Method for Large-Scale Satellite Navigation and Positioning Reference Stations[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1609-1619. DOI: 10.13203/j.whugis20210202
Citation: SHU Bao, HE Yuanhao, WANG Li, ZHOU Xing, ZHANG Qin, HUANG Guanwen. A Network RTK Method for Large-Scale Satellite Navigation and Positioning Reference Stations[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1609-1619. DOI: 10.13203/j.whugis20210202

一种适用于大尺度卫星导航定位基准站的网络RTK方法

A Network RTK Method for Large-Scale Satellite Navigation and Positioning Reference Stations

  • 摘要: 网络实时动态测量(real-time kinematic, RTK)技术可为大范围区域用户提供实时高精度的定位服务,然而目前该技术对卫星导航定位(satellite navigation and positioning,SNAP)基准站网密度要求较高。为了满足稀疏大尺度SNAP基准站网区域的高精度定位服务需求,提出了一种基于虚拟大气约束(virtual atmosphere constrait, VAC)的网络RTK服务方法,首先构建非组合双差观测值模型,快速解算并固定SNAP基准站基线模糊度;然后提取基线大气延迟,分别建立斜路径电离层和天顶对流层误差模型;最后将内插的大气延迟及其精度信息作为虚拟观测值,提升终端RTK的定位性能。采用中国西北的SNAP基准站网数据(平均站间距为205.1 km)和网内外6个流动站数据进行RTK验证,结果表明,所提方法可以满足大尺度参考网下用户的高精度定位需求,相比传统的虚拟基准站技术,VAC服务模式下的终端定位精度、初始化速度平均分别提升61.64%和9.96%,该模式下测试终端固定解水平和高程方向的平均均方根分别为1.19 cm、2.73 cm;采用多次初始化进行验证,平均88.78%的时段在2个历元内即可完成初始化;VAC服务模式对大尺度SNAP基准站网内外用户均具有较好的适应性。

     

    Abstract:
      Objectives  Network real-time kinematic (RTK) technology can provide real-time and high-precision positioning service for users over the wide range, however, the current technology depends on high density of satellite navigation and positioning (SNAP) reference station network. To satisfy the high-precision positioning requirements based on the sparse reference station network, this paper recommends a network RTK service method based on virtual atmosphere constrait(VAC).
      Methods  Firstly, a non-combined double-difference observation model is constructed to solve and fix the network RTK baseline ambiguity quickly. Then, the baseline atmospheric delay is extracted and the slant path ionosphere and zenith tropsphere are established respectively. Finally, the interpolated atmospheric delay and its accuracy information are regarded as virtual observations to improve the positioning performance of the terminal RTK. Based on a 205.1 km station spacing SNAP network from a northwest region, China, six rover stations inside and outside the network are used for termininal RTK verification.
      Results  The results show that the VAC network RTK service method can meet the needs of high-precision positioning users over large-scale reference networks. The terminal positioning accuracy and initialization speed by the VAC method are significantly improved by 61.64% and 9.96% compared with the traditional virtual reference station method. In this service mode, the average horizontal and vertical root mean squares of the fixed solution for the six terminals are 1.19 cm and 2.73 cm. Initializing RTK solution by a lot of times, 88.78% of periods can be fixed within 2 epochs for the six rover staions.
      Conclusions  The VAC service mode has good adaptability to both users inside and outside the large-scale SNAP base station network.

     

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