利用GPT3模型的GNSS⁃PWV计算方法  

GNSS⁃PWV calculation method based on the GPT⁃3 model

作　　者：高颖 许思怡 李黎 卢厚贤 何琦敏 王晓明 GAO Ying;XU Siyi;LI Li;LU Houxian;HE Qimin;WANG Xiaoming(School of Geography Science and Geomatics Engineering,Suzhou University of Science and Technology,Suzhou 215009,China;Research Center of BeiDou Navigation and Environmental Remote Sensing,Suzhou University of Science and Technology,Suzhou 215009,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China)

机构地区：[1]苏州科技大学地理科学与测绘工程学院,江苏苏州215009 [2]苏州科技大学北斗导航与环境感知研究中心,江苏苏州215009 [3]中国科学院空天信息创新研究院,北京100094

出　　处：《测绘通报》2023年第3期44-48,103,共6页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(41904033)。

摘　　要：针对部分GNSS测站缺乏实测气象参数时无法实时计算可降水量(PWV)的问题,本文以长三角地区为例提出一种将GPT3模型参数与GNSS对流层总延迟(ZTD)融合获取高精度PWV的新方法。研究结果表明,GPT3模型的气象参数和各类对流层延迟参数在长三角地区具有较好的稳定性和精度,融合GPT3模型的干延迟(ZHD)、加权平均温度(Tm)和GNSS⁃ZTD所得PWV的RMS为3.56 mm,接近GNSS⁃PWV的3.74 mm,远优于GPT3⁃PWV的11.12 mm。To solve the problem that precipitable water vapor(PWV)can't be calculated in real time without the measured meteorological parameters at some GNSS stations,taking the Yangtze River Delta region as an example,a new method to obtain high⁃precision PWV by combining GPT3 model with GNSS⁃ZTD is proposed in this paper.The results show that the meteorological parameters and some tropospheric delay parameters of GPT3 model have good stability and accuracies in the Yangtze River Delta region.The RMS of PWV obtained by integrating the parameters(ZHD and Tm)of GPT3 model and GNSS⁃ZTD is 3.56 mm,which is close to GNSS⁃PWV(3.74 mm),and is far superior to GPT3⁃PWV(11.12 mm).

关 键 词：GNSS PWV GPT3模型 融合 

分 类 号：P228[天文地球—大地测量学与测量工程]