对流层映射函数对GNSS反演可降水量的影响分析

对流层映射函数是将对流层天顶延迟转化为信号传播路径上总延迟的重要模型,选择合适的映射函数对反演大气可降水量(PWV)精度的提高具有十分重要的意义．本文研究了对流层映射函数对反演PWV精度的影响,选取VMF1、GMF、NMF 3种映射函数,利用GAMIT解算比较3种映射函数在不同季节、不同高度角对网基线解算以及反演PWV的精度影响．结果表明,在进行PWV反演时,选择10°高度角作为解算截止高度角的GMF函数模型反演精度最佳,为进一步提高GNSS水汽反演的实时精度提供了参考．      

融合大气数值模式的高精度对流层天顶延迟计算方法

针对现有对流层天顶延迟模型改正法因水汽参数难以精确获取所导致的时空分辨率与精度上的不足问题,提出了一种融合WRF(weather research and forecasting model)大气数值模式的对流层天顶延迟估计方法。通过分析WRF模式的数值模拟机理及其数据结构特征,采用直接积分与模型改正相结合的混合计算方式,实现了全球任意位置上小时级的对流层天顶延迟估计。验证结果表明,该方法计算的小时级ZTD再分析值精度为13.6mm,日均值精度更是可达9.3mm,比传统模型UNB3m的49.6mm以及目前标称精度最高模型GPT2w的34.6mm,精度分别提高了约5倍和3.5倍。在30h的预报时段内,预报值精度也可达22mm。无论是ZTD再分析值还是预报值比现有模型的估计值精度均有明显提高。     

GPS对流层延迟改正UNB3模型及其精度分析

就GPS对流层延迟改正UNB3模型的天顶延迟模型和Niell映射函数模型进行了详细的探讨,采用C 语言编程,建立了相应的程序模块;在GPS普通单点定位中,比较分析了UNB3模型的修正精度;通过IGS跟踪站的大量数据分析计算表明,UNB3天顶延迟模型的修正精度在平面x、y方向上与Saastamoinen天顶延迟模型相当,在高程H方向上优于Saastamoinen天顶延迟模型.     

一种基于机器学习算法的区域/单站ZTD组合预测模型

针对天顶对流层总延迟(ZTD)具有一定的时空变化特性,提出了一种基于BP神经网络、长短期记忆网络(LSTM)算法的区域/单站ZTD组合预测模型. 以连续14天香港连续运行参考站(CORS)网络18个监测站观测数据为例,利用BP神经网络、LSTM及本文算法进行了区域、单站及二者组合ZTD预测模型研究. HKWS测站的预测结果表明:利用前13天数据预报第14天数据,区域、单站、组合模型ZTD预测的均方根误差（RMSE）分别为10.2 mm、10.4 mm、8.5 mm,组合模型相对于区域、单站模型预测精度分别提升了17.2%、18.4%.      

An Improved Mean-Gravity Model for GPS Hydrostatic Delay Calibration

The determination of global positioning system (GPS) heights with submillimeter accuracy needs proper correction of tropospheric delay. In this letter, the modeling of zenith hydrostatic delay (ZHD) was addressed, considering that wet delay must be treated separately. ZHD is traditionally estimated from Saastamoinen's formula using a mean-gravity model and surface pressure observations. The uncertainty in ZHD associated with the mean-gravity model is about 0.3 mm. An improved parametric model is derived here, which yields an uncertainty in the ZHD less than 0.1 mm when the surface altitude lies in the range of 0-9 km. A second parametric model is derived for higher altitudes (such as above radiosonde observations or atmospheric models). Both parametric models depend on latitude, height, and time variables. This dependence is due to the link between the mean gravity and temperature profiles between the surface and ~80-km altitude. The uncertainty in the parametric models due to short-term temporal variability of the temperature profiles is shown to produce an uncertainty in ZHD smaller than 0.1 mm     

Tropospheric delay gradients from numerical weather prediction models: effects on GPS estimated parameters

Several numerical weather prediction (NWP) models provide information on the 3D state of the neutral atmosphere which has enabled GNSS researchers to have improved a priori information of the delay induced in the GNSS signals. However, the quality of weather models on the one hand and computational difficulties on the other, are motivations to develop an algorithm based partly on NWP models, while still estimating the remaining residual delay through GNSS processing strategies. An algorithm has been developed to estimate horizontal delay gradients from Meteorological Service of Canada NWP models. The GNSS software “Bernese” has also been modified to handle these gradients, as well as zenith delay and mapping functions based on NWP models in phase and code observation equations. Month-long precise point positioning results show strong correlation between north–south hydrostatic gradients and latitude differences, with significant but less strong correlation with the height and zenith total delay parameters. The longitude components were not sensitive to the implementation of gradients. High precision GNSS applications such as long term geodynamics studies, realization of terrestrial reference frames and climatology and consequential interpretations may be affected by ignoring the asymmetry of the neutral atmosphere. In addition to estimating the gradients, implementing a priori information on gradients in the processing software may have an impact on estimated results and consequential interpretations.     

GPS信号对流层延迟改正新模型研究

为削弱对流层对GPS精密定位的影响，从大气折射率入手将大气分为3层，建立了大气折射率模型，并导出了对流层天顶延迟模型。利用IGS跟踪站的实测数据进行了验证，实验证明了新模型的有效性。     

GPS测量中的大气路径延迟订正

根据上海和北京两站１９９２～１９９３两年的气象探空资料，分别计算了ＧＰＳ伪距测量中的干项和湿项订正值。在此资料样本上，用最小二乘回归拟合得到了干、湿项订正的算式。分析大气球面分层的计算结果可见，干、湿项订正值随卫星天项角（≤７５°）的变化可以很好地用Ｓｅｃａｎｔ律来表示。该算式的精度优于其他模型；不同气候地区要采用根据当地气象资料建立起的订正算式     

A real-time meteorological-based troposphere (RMT) correction with integrity bound for long baseline DGPS

This paper concentrates on the analysis of a real-time meteorological (MET)-based troposphere (RMT) model where MET data are used in real-time to provide troposphere error corrections with a bounded level of integrity for a prototype National Differential Global Positioning System-High Performance (NDGPS-HP) architecture. Toward this goal, three aspects are studied for this approach: sensitivity analysis, accuracy assessment, and integrity analysis. A Hopfield zenith delay and Chao mapping function models were chosen as a good compromise between accuracy and complexity in the integrity analysis. The sensitivity analysis results indicate that the Hopfield model is mostly sensitive to hot humid conditions, which is compounded slightly more and where some relative humidity sensors are less accurate. The accuracy assessment was performed with respect to both absolute and relative accuracy. In the absolute accuracy assessment, the comparison was made in terms of zenith troposphere delay estimation error, with respect to the International GPS Service (IGS) final troposphere zenith path delay (ZPD) product, which was used as the true ZPD. For locations where IGS stations are not available, a relative accuracy assessment was performed whereby comparisons were made in terms of GPS double difference (DD) carrier-phase troposphere correction residuals using various techniques. The accuracy assessment results indicate that the RMT has insignificant differences from the prototype National Oceanic and Atmosphere Administration (NOAA) troposphere error forecast model. An integrity analysis was performed, which presents integrity bounds for the RMT that can be applied to a NDGPS-HP architecture in which integrity requirements exist. The overriding goal of this effort was to establish a preliminary real-time troposphere error estimation model, with defined levels of integrity in its troposphere error estimation that can be included in an NDGPS-HP architecture, where integrity is a key system requirement. The conclusion is drawn that the RMT model may be well suited for a variety of users within a NDGPS-HP architecture. An erratum to this article can be found at     

Atmospheric modelling in GPS analysis and its effect on the estimated geodetic parameters

Permanently operating Global Positioning System (GPS) receivers are used today, for example, in precise positioning and determination of atmospheric water vapour content. The GPS signals are delayed by various gases when traversing the atmosphere. The delay due to water vapour, the wet delay, is difficult to model using ground surface data and is thus often estimated from the GPS data. In order to obtain the most accurate results from the GPS processing, a modelling of the horizontal distribution of the wet delay may be necessary. Through simulations, three such models are evaluated, one of which is developed in this paper. In the first model the water vapour is assumed to be horizontally stratified, thus the wet delay can be described by only one zenith parameter. The second model gives the wet delay with one zenith and two horizontal gradient parameters. The third model uses the correlation between the wet-delay values in different directions. It is found that for large gradients and strong turbulence the two latter models yield lower errors in the estimated vertical coordinate and wet-delay parameters. For large gradients this improvement is up to 7 mm in the zenith wet-delay parameter, from 9 mm down to 2 and 4 mm for the second and third models, respectively. Received: 7 May 1998 / Accepted: 1 March 1999     

大气折射延迟映射函数的比较

简要综述对流层大气折射延迟的基本概念,对几种常用的连分式的映射函数进行比较,结果表明映射函数模型在低高度角呈现较大的差异性,说明利用映射函数模型对大气折射进行改正有很多局限性。     

Interpolating atmospheric water vapor delay by incorporating terrain elevation information

In radio signal-based observing systems, such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR), the water vapor in the atmosphere will cause delays during the signal transmission. Such delays vary significantly with terrain elevation. In the case when atmospheric delays are to be eliminated from the measured raw signals, spatial interpolators may be needed. By taking advantage of available terrain elevation information during spatial interpolation process, the accuracy of the atmospheric delay mapping can be considerably improved. This paper first reviews three elevation-dependent water vapor interpolation models, i.e., the Best Linear Unbiased Estimator in combination with the water vapor Height Scaling Model (BLUE + HSM), the Best Linear Unbiased Estimator coupled with the Elevation-dependent Covariance Model (BLUE + ECM), and the Simple Kriging with varying local means based on the Baby semi-empirical model (SKlm + Baby for short). A revision to the SKlm + Baby model is then presented, where the Onn water vapor delay model is adopted to substitute the inaccurate Baby semi-empirical model (SKlm + Onn for short). Experiments with the zenith wet delays obtained through the GPS observations from the Southern California Integrated GPS Network (SCIGN) demonstrate that the SKlm + Onn model outperforms the other three. The RMS of SKlm + Onn is only 0.55 cm, while those of BLUE + HSM, BLUE + ECM and SKlm + Baby amount to 1.11, 1.49 and 0.77 cm, respectively. The proposed SKlm + Onn model therefore represents an improvement of 29–63% over the other known models.     

卫星遥感大气订正的参数化模式及其模拟应用

发展了一个用于卫星大气订正的参数化模式,包括一个新的程辐射亮度模式和一个参数化的朗伯地表一大气辐射耦合引起的亮度增量模式.应用最小二乘法,程辐射亮度被参数化为大气总光学厚度、一次散射反照率、太阳天顶角、视天顶角、方位角、大气不对称因子的函数.应用这一参数化的亮度模式进行大气订正应用的数值模拟,即进行卫星遥感地表光谱反照率的模拟试验.数值检验结果表明对于865 nm,670nm,550nm和412nm 4个MODIS通道,在0°-70°的太阳天顶角、0°-60°视观测角以及0.05-0.8的地表反照率条件下,参数化的向上辐射亮度的标准差小于4%,由该参数化亮度模式引起的地表反照率解的标准差小于0.03.     

提高对流层天顶总延迟解算精度的新方法探讨

对流层天顶总延迟的解算精度,直接影响长基线解算的精度和大气水汽含量的计算精度。文中提出克利金内插法解算天顶总延迟的新方法,并利用南极长城站和周边IGS跟踪站的GPS数据,通过高精度解算软件GAMIT/GLOBK,解算出长城站上空的对流层天顶总延迟,将其与利用内插方法解算的天顶总延迟进行了对比分析,得出:利用该内插方法获取的南极长城站在夏季的天顶总延迟的均方差可达0.2mm,这对今后GPS高精度定位和GPS气象学应用来说,具有重要意义。     

天文大气折射改正模型比较分析

天文大气折射一直是影响天文测量精度的主要因素之一,针对光学天文测量中大气折射的问题,主要介绍、归纳了几种在处理天文大气折射改正中常用的模型,并比较分析了标准大气条件下不同模型的改正效果,为天文大气折射模型改正的进一步研究提供基础。结果表明:在天顶距不大于60°的情况下,不同方法之间差异性很小,但随着天顶距的增大,不同方法的差异增大。对于高精度天文测量,需要寻求一种精度高、实用性强的处理方法对天文大气折射的影响进行改正和计算。      

SBDART的参数化短波辐射传输模型

云层对地气系统辐射能量平衡有重要的调节作用,然而传统1维大气辐射传输模型仅能考虑晴空和全云两种情况。为了更好地研究云层对地表短波辐射的影响,以大气辐射传输模型SBDART(Santa Barbara Disort Atmospheric Radiative Transfer)为基础,在短波辐射传输基本方程中引入半球天空有效云覆盖度和区域真实云覆盖度两个关键云参数,考虑太阳方向和半球天空云层覆盖情况,对模型进行几何关系的修正。结合短波辐射的影响因素和SBDART模型的内置参数,选择13个参数,使用全局定量敏感性分析软件Sim Lab对修正后的模型进行参数敏感性分析及应用讨论。研究结果表明:该模型能够较好地描述云层对地表短波辐射的影响;对下行短波辐射和地表短波净辐射而言,太阳天顶角和地表反照率的影响最为显著;两个云覆盖参数在很大程度上也影响了地表短波辐射分量;在模型实际应用过程中,敏感性较强的6个参数均可以通过卫星遥感数据得到,模型具有较好的应用前景。由此可见,改进的短波辐射传输模型能够更好地考虑不同云层条件下、不同太阳–云–观测几何下的短波辐射传输问题,有利于提高短波辐射参量的遥感反演精度。     

基于非差非组合PPP-RTK的大气改正模型及其性能验证

高精度的大气改正是加快PPP-RTK收敛的重要前提。本文以区域跟踪网台站数据为基础,基于非差非组合PPP提取斜路径电离层和天顶对流层延迟,作为PPP-RTK大气建模的数据源。电离层延迟采用基于斜路径星间单差的改正模型,对流层采用非差天顶对流层模型,设计了相关的服务端和用户端软件系统。在系统设计上,通过服务端提取数据构建大气模型并播发,用户端接收参数并用于实时PPP-RTK定位。对上海区域进行服务端和用户端的试验,服务端计算的参数表明：GPS、GALILEO、BDS系统的电离层、对流层模型内符合精度为6~7 mm。用户端的646组PPP-RTK伪动态试验表明：水平方向30 s内收敛的占比为89.16%、1 min内收敛的占比为91.80%、2 min内收敛的占比为95.98%;三维方向收敛结果中,上述收敛时间尺度分别占总数的86.22%、88.70%和93.34%。附加大气约束后,模糊度固定率为95.59%,收敛后水平方向和三维方向定位RMSE分别为2.35和4.63 cm。实时动态试验表明,PPP首次固定时间为36 s,水平和三维定位精度分别达到了1.13和3.21 cm。     

Forecast Vienna Mapping Functions 1 for real-time analysis of space geodetic observations

The Vienna Mapping Functions 1 (VMF1) as provided by the Institute of Geodesy and Geophysics (IGG) at the Vienna University of Technology are the most accurate mapping functions for the troposphere delays that are available globally and for the entire history of space geodetic observations. So far, the VMF1 coefficients have been released with a time delay of almost two days; however, many scientific applications require their availability in near real-time, e.g. the Ultra Rapid solutions of the International GNSS Service (IGS) or the analysis of the Intensive sessions of the International VLBI Service (IVS). Here we present coefficients of the VMF1 as well as the hydrostatic and wet zenith delays that have been determined from forecasting data of the European Centre for Medium-Range Weather Forecasts (ECMWF) and provided on global grids. The comparison with parameters derived from ECMWF analysis data shows that the agreement is at the 1 mm level in terms of station height, and that the differences are larger for the wet mapping functions than for the hydrostatic mapping functions and the hydrostatic zenith delays. These new products (VMF1-FC and hydrostatic zenith delays from forecast data) can be used in real-time analysis of geodetic data without significant loss of accuracy.     

GPS-PWV estimation and validation with radiosonde data and numerical weather prediction model in Antarctica

Three permanent GPS tracking stations in the trans Antarctic mountain deformation (TAMDEF) network were used to estimate precipitable water vapor (PWV) using measurement series covering the period of 2002–2005. TAMDEF is a National Science Foundation funded joint project between The Ohio State University and the United States Geological Survey. The TAMDEF sites with the longest GPS data spans considered in this research are Franklin Island East (FIE0), the International GNSS Service site McMurdo (MCM4), and Cape Roberts (ROB1). For the experiment, PWV was extracted from the ionosphere-free double-difference carrier phase observations, processed using the adjustment of GPS ephemerides (PAGES) software. The GPS data were processed with a 30 s sampling rate, 15-degree cutoff angle, and precise GPS orbits disseminated by IGS. The time-varying part of the zenith wet delay is estimated using the Marini mapping function, while the constant part is evaluated using the corresponding Marini tropospheric model. Previous studies using TAMDEF data for PWV estimation show that the Marini mapping function performs the best among the models offered by PAGES. The data reduction to compute the zenith wet delay follows the step piecewise linear strategy, which is subsequently transformed to PWV. The resulting GPS-based PWV is compared to the radiosonde observations and to values obtained from the Antarctic mesoscale prediction system (AMPS). This comparison revealed a consistent bias of 1.7 mm between the GPS solution and the radiosonde and AMPS reference values.     

GPS气象学中垂直干分量延时的精确确定

确定大气中可降水分的含量是ＧＰＳ气象学的目的之一。可降水分含量对应于ＧＰＳ信号中湿分量延时。现有高精度ＧＰＳ软件包只能提供天顶方向的对流层延时,但是,对流层延时由干分量和湿分量延时组成。因此,精确确定干分量延时,是分离湿分量延时的关键,也是ＧＰＳ气象学中必不可少的工作。现有３种经验模型计算垂直干分量延时,即萨氏（Ｓａａｓｔａｍｏｉｎｅｎ）模型,霍氏（Ｈｏｐｆｉｅｌｄ）模型和布兰克（Ｂｌａｃｋ）模型