多模型融合的对流层天顶延迟估计方法  

Multi-model Fusion Method to Estimate Zenith Tropospheric Delay

作　　者：雷雨 赵丹宁 徐劲松 蔡宏兵 Lei Yu;Zhao Danning;Xu Jinsong;Cai Hongbing(School of Computer of Science and Technology,Xi′an University of Posts and Communications,Xi′an 710121,China,Email:[e-mail];School of Electrical and Electronic Engineering,Baoji University of Arts and Sciences,Baoji 721016,China;JSNU SPBPU institute of Engineering,Xuzhou 221116,China)

机构地区：[1]西安邮电大学计算机学院,陕西西安710121 [2]宝鸡文理学院电子电气工程学院,陕西宝鸡721016 [3]江苏师范大学圣理工学院,江苏徐州221116

出　　处：《天文研究与技术》2023年第2期111-122,共12页Astronomical Research & Technology

基　　金：陕西省基础科学研究计划(2022JM-031);徐州市重点研发计划(KC18079)资助.

摘　　要：为提高对流层天顶延迟(Zenith Tropospheric Delay,ZTD)估计精度,基于传统对流层天顶延迟建模思路,提出Saastamoinen,Askne和GPT3多模型融合的对流层天顶延迟估计方法。分别采用Saastamoinen和Askne模型估计干延迟和湿延迟,并引入GPT3模型提供温度、气压、水汽压、大气加权平均温度和水汽垂直递减率等气象参数。利用全球大地测量观测系统(Global Geodetic Observing System,GGOS)Atmosphere和国际GNSS服务机构(International GNSS Service,IGS)提供的亚洲区域2016~2018年66个IGS站的对流层天顶延迟数据对本文方法进行评估,结果表明,以GGOS Atmospheres数据为参考时,Sas+Ask+GPT3模型精度(均方根为4.53 cm)较同等条件下的Sas+Ask+UNB3m和Sas+GPT3模型分别提高约29%和19%,以IGS对流层天顶延迟数据为参考时,Sas+Ask+GPT3模型精度(均方根为4.35 cm)较另两种模型分别提高约25%和14%。Sas+Ask+GPT3模型误差具有冬季小、夏季大的季节性特征,且夏季误差明显低于另两种模型。在空间分布上,模型误差随高程或纬度的增加而降低。研究表明,本文方法可用于亚洲区域对流层天顶延迟的高精度实时修正。This paper proposes a method fusing GPT3,Saastamoinen and Askne models to improve the estimation accuracy of zenith tropospheric delay(ZTD)based on the conventional modeling strategy.In this method,Saastamoinen and Askne models are used to estimate zenith hydrostatic and wet delay respectively,and GPT3 model is employed to provide the meteorological parameters including temperature,pressure,water vapor pressure,weighted temperature and vertical gradient of water vapor required by the two models.The ZTD data in the the International GNSS Service(IGS)Asia stations from 2016 to 2018 published by the Global Geodetic Observing System(GGOS)atmosphere and IGS are used to evaluate this proposed method.The results indicate that the accuracy(RMS:4.53 cm)of the Sas+Ask+GPT3 model is about 29%and 19%higher than that of Sas+Ask+UNB3m and Sas+GPT3 models respectively when the ZTD data from the GGOS atmosphere are served as a reference.When the IGS ZTD products are used as a reference,the accuracy(RMS:4.35 cm)of the model is about 25%and 14%higher than that of the other two models,respectively.The bias and RMS of the ZTD estimates is more larger in summer than in winter,showing that the error has a seasonal characteristics.However,the error in summer is significantly lower than the other two models.In addition,it is also shown that the bias and RMS decrease with the increase of altitude or latitude.Especially,the error in high-altitude stations is substantially lower than that of the Sas+Ask+UNB3m model.It is concluded that the proposed method is more potential to accurately estimate ZTD in Asia areas and therefore can be used for real-time ZTD correction over Asia.

关 键 词：对流层天顶延迟 GPT3模型 UNB3m模型 Saastamoinen模型 Askne模型 

分 类 号：P228.4[天文地球—大地测量学与测量工程]