基于气象要素内插的地基GPS/PWV方法研究与精度分析  

Method and precision analysis of GPS/PWV sensing based on meteorological elements interpolation

作　　者：申建华 SHEN Jianhua(Shanghai Surveying and Mapping Institute,Shanghai 200063,China)

机构地区：[1]上海市测绘院,上海200063

出　　处：《全球定位系统》2020年第3期89-95,共7页Gnss World of China

摘　　要：测站气压和温度的准确获取对GPS水汽反演的精度至关重要,但是我国各地在建立GPS连续运行观测站时的发展状态差别较大,有相当部分的GPS气象站网并未配备气压和温度传感器,无法有效准确采集测站气压及温度相关数据,对实时获取测站上方水汽有较大影响.本文基于一种增加高度改正的反距离加权法,和分布在全国的全球卫星导航系统(GNSS)气象站网数据,对该方法进行了实验验证.实验结果表明,通过此方法得到的气压和温度参数精度满足水汽解算需要.同时将本文方法与全球气温和气压经验模型(GPT2)进行对比,证明了本文得到的温压参数精度要优于GPT2模型.Accurate acquisition of station pressure and temperature plays a vital role in the accuracy of GPS water vapor inversion,However,due to the differences in the development status of GPS continuous operation observation stations in various parts of China,A considerable part of the GPS weather station network is not equipped with pressure and temperature sensors,and failed to effectively collect accurate station pressure and temperature related data,Which has great influence on real-time acquisition of water vapor above the station,This paper proposes an inverse distance weighting method that increases altitude correction,and validates the method using GNSS weather station network data distributed throughout the country.Experimental results show that the accuracy of the pressure and temperature parameters obtained by this method meets the needs of water vapor solution.At the same time,the method mentioned in this article is compared with the GPT2 temperature and pressure model,which proves that the accuracy of the temperature and pressure parameters obtained in this paper is better than that of the GPT2 weather model.

关 键 词：全球定位系统 反距离加权 大气水汽 气象参数 内插半径 

分 类 号：P228.49[天文地球—大地测量学与测量工程]