测绘学报 ›› 2021, Vol. 50 ›› Issue (5): 685-694.doi: 10.11947/j.AGCS.2021.20200515

• 地图学与地理信息 • 上一篇    下一篇

全球ZWD垂直剖面滑动窗口的格网模型

黄良珂1,2, 朱葛1,2, 彭华1,2, 陈华3, 刘立龙1,2, 姜卫平4   

  1. 1. 桂林理工大学测绘地理信息学院, 广西 桂林 541004;
    2. 广西空间信息与测绘重点实验室, 广西 桂林 541004;
    3. 武汉大学测绘学院, 湖北 武汉 430079;
    4. 武汉大学卫星导航定位技术研究中心, 湖北 武汉 430079
  • 收稿日期:2020-10-20 修回日期:2021-03-15 发布日期:2021-06-03
  • 通讯作者: 刘立龙 E-mail:hn_liulilong@163.com
  • 作者简介:黄良珂(1986-),男,博士,副教授,研究方向为GNSS气象学。E-mail:lkhuang666@163.com
  • 基金资助:
    国家自然科学基金(41704027;41864002;41664002);广西自然科学基金(2017GXNSFBA198139;2017GXNSFDA198016;2018GXNSFAA281182);国家重点研发计划(SQ2018YFC150052);广西空间信息与测绘重点实验室资助课题(19-050-11-02);湖南省自然资源调查与监测工程技术研究中心开放课题(2020-9);广西“八桂学者”岗位专项

A global grid model for the vertical correction of zenith wet delay based on the sliding window algorithm

HUANG Liangke1,2, ZHU Ge1,2, PENG Hua1,2, CHEN Hua3, LIU Lilong1,2, JIANG Weiping4   

  1. 1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;
    2. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China;
    3. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    4. GNSS Research Center, Wuhan University, Wuhan 430079, China
  • Received:2020-10-20 Revised:2021-03-15 Published:2021-06-03
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41704027;41864002;41664002);The Guangxi Natural Science Foundation of China (Nos. 2017GXNSFBA198139;2017GXNSFDA198016;2018GXNSFAA281182);The National Key Research and Development Program (No. SQ2018YFC150052);The Guangxi Key Laboratory of Spatial Information and Geomatics (No. 19-050-11-02);The Open Fund of Hunan Natural Resources Investigation and Monitoring Engineering Technology Research Center (No. 2020-9);The "Ba Gui Scholars" Program of the Provincial Government of Guangxi

摘要: 对流层延迟是GNSS导航定位的主要误差源之一。针对已有对流层天顶湿延迟(ZWD)垂直剖面模型存在建模仅采用单一格网点数据以及使用月均剖面数据等不足,本文提出了一种基于滑动窗口的ZWD垂直剖面格网模型构建方法,建立了一种顾及精细季节变化的高精度全球ZWD垂直剖面模型(GZWD-H模型)。同时,联合2017年全球321个探空站资料,对GZWD-H模型的垂直插值及其在全球大地观测系统(GGOS)大气格网ZWD空间插值中的应用进行了精度检验,并与全球性能优异的GPT2w模型进行对比。结果表明:①以全球探空站数据积分计算的ZWD分层剖面信息为参考值,GZWD-H模型在全球ZWD的垂直插值中均表现出了最优的精度和稳定性,相对于GPT2w-1和GPT2w-5模型分别提升了4%和7%;②以全球探空站数据计算的地表ZWD信息为参考值,GZWD-H模型在GGOS大气格网ZWD产品空间插值中的精度相对于GPT2w-1和GPT2w-5模型分别提升了17%和35%;③相对于GPT2w-1模型,GZWD-H模型进一步减少和优化了模型参数。因此,GZWD-H模型在全球GNSS大气探测和GNSS精密定位中具有重要的应用。

关键词: 滑动窗口, 对流层延迟模型, 对流层湿延迟, 垂直剖面

Abstract: Tropospheric delay is an important error source in Global Navigation Satellite System (GNSS) positioning. Some shortages still exist in current global zenith wet delay (ZWD) vertical stratification models, such as only single gridded data as well as monthly profiles is used for modeling. To address those of drawbacks, a new approach, the sliding window algorithm, is proposed to develop the ZWD vertical stratification model. In this work, the ZWD vertical stratification model that considering seasonal variations of ZWD height scale factor is developed, named as GZWD-H model. The ZWD layered profiles from 321 radiosonde sites in 2017 are treated as reference values, to evaluate the performance of GZWD-H model in layered vertical interpolation and its application in spatial interpolation for GGOS (global geodetic observing system) atmosphere gridded ZWD. Besides, the performance of GZWD-H model is compared to the GPT2w model. The results show that GZWD-H model shows the best performance in the ZWD layered vertical interpolation against the ZWD layered profiles from globally distributed radiosonde sites. In terms of RMS, the GZWD-H model has improved by 4% and 7% compared to the GPT2w-1 and GPT2w-5 models, respectively. Compared to GPT2w-1 and GPT2w-5 models, GZWD-H model has improved by 17% and 35% in spatial interpolation for GGOS Atmosphere gridded ZWD against surface ZWD calculated from radiosonde profiles over globe, respectively. In terms of model parameters, GZWD-H model has been significantly reduced and optimized against GPT2w-1 model, thus, the applicability of this model could be enhanced in GNSS atmospheric sounding and GNSS precise position.

Key words: sliding window algorithm, tropospheric delay model, zenith wet delay, vertical stratification

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