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1.
This paper compares estimates of station coordinates from global GPS solutions obtained by applying different troposphere
models: the Global Mapping Function (GMF) and the Vienna Mapping Function 1 (VMF1) as well as a priori hydrostatic zenith
delays derived from the Global Pressure and Temperature (GPT) model and from the European Centre for Medium-Range Weather
Forecasts (ECMWF) numerical weather model data. The station height differences between terrestrial reference frames computed
with GMF/GPT and with VMF1/ECMWF are in general below 1 mm, and the horizontal differences are even smaller. The differences
of annual amplitudes in the station height can also reach up to 1 mm. Modeling hydrostatic zenith delays with mean (or slowly
varying empirical) pressure values instead of the true pressure values results in a partial compensation of atmospheric loading.
Therefore, station height time series based on the simple GPT model have a better repeatability than those based on more realistic
ECMWF troposphere a priori delays if atmospheric loading corrections are not included. On the other hand, a priori delays
from numerical weather models are essential to reveal the full atmospheric loading signal. 相似文献
2.
Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of \(3^{\circ }\). Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a \(5^{\circ }\times 5^{\circ }\) as well as a \(1^{\circ }\times 1^{\circ }\) global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3. 相似文献
3.
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． 相似文献
4.
Volker Tesmer Johannes Boehm Robert Heinkelmann Harald Schuh 《Journal of Geodesy》2007,81(6-8):409-421
This paper compares estimated terrestrial reference frames (TRF) and celestial reference frames (CRF) as well as position time-series in terms of systematic differences, scale, annual signals and station position repeatabilities using four different tropospheric mapping functions (MF): The NMF (Niell Mapping Function) and the recently developed GMF (Global Mapping Function) consist of easy-to-handle stand-alone formulae, whereas the IMF (Isobaric Mapping Function) and the VMF1 (Vienna Mapping Function 1) are determined from numerical weather models. All computations were performed at the Deutsches Geodätisches Forschungsinstitut (DGFI) using the OCCAM 6.1 and DOGS-CS software packages for Very Long Baseline Interferometry (VLBI) data from 1984 until 2005. While it turned out that CRF estimates only slightly depend on the MF used, showing small systematic effects up to 0.025 mas, some station heights of the computed TRF change by up to 13 mm. The best agreement was achieved for the VMF1 and GMF results concerning the TRFs, and for the VMF1 and IMF results concerning scale variations and position time-series. The amplitudes of the annual periodical signals in the time-series of estimated heights differ by up to 5 mm. The best precision in terms of station height repeatability is found for the VMF1, which is 5–7% better than for the other MFs. 相似文献
5.
Numerical simulation of troposphere-induced errors in GPS-derived geodetic time series over Japan 总被引：2，自引：2，他引：0
Troposphere-induced errors in GPS-derived geodetic time series, namely, height and zenith total delays (ZTDs), over Japan
are quantitatively evaluated through the analyses of simulated GPS data using realistic cumulative tropospheric delays and
observed GPS data. The numerical simulations show that the use of a priori zenith hydrostatic delays (ZHDs) derived from the
European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather model data and gridded Vienna mapping function
1 (gridded VMF1) results in smaller spurious annual height errors and height repeatabilities (0.45 and 2.55 mm on average,
respectively) as compared to those derived from the global pressure and temperature (GPT) model and global mapping function
(GMF) (1.08 and 3.22 mm on average, respectively). On the other hand, the use of a priori ZHDs derived from the GPT and GMF
would be sufficient for applications involving ZTDs, given the current discrepancies between GPS-derived ZTDs and those derived
from numerical weather models. The numerical simulations reveal that the use of mapping functions constructed with fine-scale
numerical weather models will potentially improve height repeatabilities as compared to the gridded VMF1 (2.09 mm against
2.55 mm on average). However, they do not presently outperform the gridded VMF1 with the observed GPS data (6.52 mm against
6.50 mm on average). Finally, the commonly observed colored components in GPS-derived height time series are not primarily
the result of troposphere-induced errors, since they become white in numerical simulations with the proper choice of a priori
ZHDs and mapping functions. 相似文献
6.
Testing of global pressure/temperature (GPT) model and global mapping function (GMF) in GPS analyses 总被引：1，自引：1，他引：0
J. Kouba 《Journal of Geodesy》2009,83(3-4):199-208
Several sources of a priori meteorological data have been compared for their effects on geodetic results from GPS precise point positioning (PPP). The new global pressure and temperature model (GPT), available at the IERS Conventions web site, provides pressure values that have been used to compute a priori hydrostatic (dry) zenith path delay z h estimates. Both the GPT-derived and a simple height-dependent a priori constant z h performed well for low- and mid-latitude stations. However, due to the actual variations not accounted for by the seasonal GPT model pressure values or the a priori constant z h, GPS height solution errors can sometimes exceed 10 mm, particularly in Polar Regions or with elevation cutoff angles less than 10 degrees. Such height errors are nearly perfectly correlated with local pressure variations so that for most stations they partly (and for solutions with 5-degree elevation angle cutoff almost fully) compensate for the atmospheric loading displacements. Consequently, unlike PPP solutions utilizing a numerical weather model (NWM) or locally measured pressure data for a priori z h, the GPT-based PPP height repeatabilities are better for most stations before rather than after correcting for atmospheric loading. At 5 of the 11 studied stations, for which measured local meteorological data were available, the PPP height errors caused by a priori z h interpolated from gridded Vienna Mapping Function-1 (VMF1) data (from a NWM) were less than 0.5 mm. Height errors due to the global mapping function (GMF) are even larger than those caused by the GPT a priori pressure errors. The GMF height errors are mainly due to the hydrostatic mapping and for the solutions with 10-degree elevation cutoff they are about 50% larger than the GPT a priori errors. 相似文献
7.
Forecast Vienna Mapping Functions 1 for real-time analysis of space geodetic observations 总被引：3，自引：2，他引：1
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. 相似文献
8.
J. Kouba 《Journal of Geodesy》2008,82(4-5):193-205
The new gridded Vienna Mapping Function (VMF1) was implemented and compared to the well-established site-dependent VMF1, directly
and by using precise point positioning (PPP) with International GNSS Service (IGS) Final orbits/clocks for a 1.5-year GPS
data set of 11 globally distributed IGS stations. The gridded VMF1 data can be interpolated for any location and for any time
after 1994, whereas the site-dependent VMF1 data are only available at selected IGS stations and only after 2004. Both gridded
and site-dependent VMF1 PPP solutions agree within 1 and 2 mm for the horizontal and vertical position components, respectively,
provided that respective VMF1 hydrostatic zenith path delays (ZPD) are used for hydrostatic ZPD mapping to slant delays. The
total ZPD of the gridded and site-dependent VMF1 data agree with PPP ZPD solutions with RMS of 1.5 and 1.8 cm, respectively.
Such precise total ZPDs could provide useful initial a priori ZPD estimates for kinematic PPP and regional static GPS solutions.
The hydrostatic ZPDs of the gridded VMF1 compare with the site-dependent VMF1 ZPDs with RMS of 0.3 cm, subject to some biases
and discontinuities of up to 4 cm, which are likely due to different strategies used in the generation of the site-dependent
VMF1 data. The precision of gridded hydrostatic ZPD should be sufficient for accurate a priori hydrostatic ZPD mapping in
all precise GPS and very long baseline interferometry (VLBI) solutions. Conversely, precise and globally distributed geodetic
solutions of total ZPDs, which need to be linked to VLBI to control biases and stability, should also provide a consistent
and stable reference frame for long-term and state-of-the-art numerical weather modeling. 相似文献
9.
10.
11.
Assessment of ECMWF-derived tropospheric delay models within the EUREF Permanent Network 总被引：1，自引：0，他引：1
The Global Positioning System (GPS) observations from the EUREF Permanent Network (EPN) are routinely analyzed by the EPN
analysis centers using a tropospheric delay modeling based on standard pressure values, the Niell Mapping Functions (NMF),
a cutoff angle of 3° and down-weighting of low elevation observations. We investigate the impact on EPN station heights and
Zenith Total Delay (ZTD) estimates when changing to improved models recommended in the updated 2003 International Earth Rotation
and Reference Systems Service (IERS) Conventions, which are the Vienna Mapping Functions 1 (VMF1) and zenith hydrostatic delays
derived from numerical weather models, or the empirical Global Mapping Functions (GMF) and the empirical Global Pressure and
Temperature (GPT) model. A 1-year Global Positioning System (GPS) data set of 50 regionally distributed EPN/IGS (International
GNSS Service) stations is processed. The GPS analysis with cutoff elevation angles of 3, 5, and 10° revealed that changing
to the new recommended models introduces biases in station heights in the northern part of Europe by 2–3 mm if the cutoff
is lower than 5°. However, since large weather changes at synoptic time scales are not accounted for in the empirical models,
repeatability of height and ZTD time series are improved with the use of a priori Zenith Hydrostatic Delays (ZHDs) derived
from numerical weather models and VMF1. With a cutoff angle of 3°, the repeatability of station heights in the northern part
of Europe is improved by 3–4 mm. 相似文献
12.
13.
14.
The empirical model GPT (Global Pressure and Temperature), which is based on spherical harmonics up to degree and order nine,
provides pressure and temperature at any site in the vicinity of the Earth’s surface. It can be used for geodetic applications
such as the determination of a priori hydrostatic zenith delays, reference pressure values for atmospheric loading, or thermal
deformation of Very Long Baseline Interferometry (VLBI) radio telescopes. Input parameters of GPT are the station coordinates
and the day of the year, thus also allowing one to model the annual variations of the parameters. As an improvement compared
with previous models, it reproduces the large pressure anomaly over Antarctica, which can cause station height errors in the
analysis of space-geodetic data of up to 1 cm if not considered properly in troposphere modelling. First tests at selected
geodetic observing stations show that the pressure biases considerably decrease when using GPT instead of the very simple
approaches applied to various Global Navigation Satellite Systems (GNSS) software packages so far. GPT also provides an appropriate
model for the annual variability of global temperature.
Electronic supplementary material The online version of this article (doi: contains supplementary material, which is available to authorized users. 相似文献
15.
Missing or incorrect consideration of azimuthal asymmetry of troposphere delays is a considerable error source in space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). So-called horizontal troposphere gradients are generally utilized for modeling such azimuthal variations and are particularly required for observations at low elevation angles. Apart from estimating the gradients within the data analysis, which has become common practice in space geodetic techniques, there is also the possibility to determine the gradients beforehand from different data sources than the actual observations. Using ray-tracing through Numerical Weather Models (NWMs), we determined discrete gradient values referred to as GRAD for VLBI observations, based on the standard gradient model by Chen and Herring (J Geophys Res 102(B9):20489–20502, 1997. https://doi.org/10.1029/97JB01739) and also for new, higher-order gradient models. These gradients are produced on the same data basis as the Vienna Mapping Functions 3 (VMF3) (Landskron and Böhm in J Geod, 2017. https://doi.org/10.1007/s00190-017-1066-2), so they can also be regarded as the VMF3 gradients as they are fully consistent with each other. From VLBI analyses of the Vienna VLBI and Satellite Software (VieVS), it becomes evident that baseline length repeatabilities (BLRs) are improved on average by 5% when using a priori gradients GRAD instead of estimating the gradients. The reason for this improvement is that the gradient estimation yields poor results for VLBI sessions with a small number of observations, while the GRAD a priori gradients are unaffected from this. We also developed a new empirical gradient model applicable for any time and location on Earth, which is included in the Global Pressure and Temperature 3 (GPT3) model. Although being able to describe only the systematic component of azimuthal asymmetry and no short-term variations at all, even these empirical a priori gradients slightly reduce (improve) the BLRs with respect to the estimation of gradients. In general, this paper addresses that a priori horizontal gradients are actually more important for VLBI analysis than previously assumed, as particularly the discrete model GRAD as well as the empirical model GPT3 are indeed able to refine and improve the results. 相似文献
16.
17.
Thomas Hobiger Youhei Kinoshita Shingo Shimizu Ryuichi Ichikawa Masato Furuya Tetsuro Kondo Yasuhiro Koyama 《Journal of Geodesy》2010,84(9):537-546
Numerical weather models offer the possibility to compute corrections for a variety of space geodetic applications, including
remote sensing techniques like interferometric SAR. Due to the computational complexity, exact ray-tracing is avoided in many
cases and mapping approaches are applied to transform vertically integrated delay corrections into slant direction. Such an
approach works well as long as lateral atmospheric gradients are small enough to be neglected. But since such an approximation
holds only for very rare cases it is investigated how horizontal gradients of different atmospheric constituents can evoke
errors caused by the mapping strategy. Moreover, it is discussed how sudden changes of wet refractivity can easily lead to
millimeter order biases when simplified methods are applied instead of ray-tracing. By an example, based on real InSAR data,
the differences of the various troposphere correction schemes are evaluated and it is shown how the interpretation of the
geophysical signals can be affected. In addition, it is studied to which extend troposphere noise can be reduced by applying
the exact ray-tracing solution. 相似文献
18.
19.
The accuracy of conventional global navigation satellite systems (GNSS) positioning in dense urban areas is severely degraded due to blockage and reflection of the signals by the surrounding buildings. By using 3D mapping of the buildings to aid GNSS positioning, the accuracy can be substantially improved. However, positioning performance must be balanced against computational load. Here, a likelihood-based 3D-mapping-aided (3DMA) GNSS ranging algorithm is demonstrated that enables signals predicted to be non-line-of-sight (NLOS) to contribute to the position solution without explicitly computing the additional path delay due to NLOS reception, which is computationally expensive. Likelihoods for an array of candidate positions are computed based on the difference between the measured and predicted pseudoranges. However, a skewed distribution is assumed for those signals predicted to be NLOS on the basis that the ensuing ranging errors are always positive. An overall position solution is then extracted from the likelihood surface. GNSS measurement data have been collected at several locations in both traditional and modern dense urban environments. Horizontal root-mean-square single-epoch position accuracies of 4.7, 5.6 and 6.5 m are obtained using, respectively, a Leica Viva geodetic receiver, a u-blox EVK M8T consumer-grade receiver and a Nexus 9 tablet incorporating a smartphone GNSS antenna and a GNSS chipset that outputs pseudoranges. The corresponding accuracies using single-epoch conventional GNSS positioning are 20.5, 23.0 and 28.4 m, about a factor of four larger. The 3DMA GNSS algorithms have also been implemented in real time on a Raspberry Pi 3 at a 1-Hz update rate.
相似文献20.
Analysis of tropospheric delay prediction models: comparisons with ray-tracing and implications for GPS relative positioning 总被引：2，自引：0，他引：2
Ray-tracing is used to examine the accuracy of several well known models for tropospheric delay prediction under varying atmospheric conditions. The models considered include the Hopfield zenith delay model and related mapping functions, the Saastamoinen zenith delay model and mapping function, and three empirical mapping functions based upon the Marini continued fraction form. Modelled delays are benchmarked against ray-tracing solutions for representative atmospheric profiles at various latitudes and seasons. Numerical results are presented in light of the approximations inherent in model formulation. The effect of approximations to the temperature, pressure and humidity structure of the neutral atmosphere are considered; the impact of surface layer anomalies (i.e., inversions) on prediction accuracy is examined; and errors resulting from the neglect of ray bending are illustrated. The influence of surface meteorological parameter measurement error is examined. Finally, model adaptability to local conditions is considered. Recommendations concerning the suitability of the models for GPS relative positioning and their optimal application are made based upon the results presented. 相似文献