Establishment and Evaluation of a New Meteorological Observation-Based Grid Model for Estimating Zenith Wet Delay in Ground-Based Global Navigation Satellite System (GNSS)

Yao, Yibin; Sun, Zhangyu; Xu, Chaoqian

doi:10.3390/rs10111718

Cited by 17 publications

(7 citation statements)

References 21 publications

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“…al. [27]. At the surface level, the TZTD model have a RMSE of 20 mm which is very close to that of the GPT3 model, and outperforms UNB3m (with a RMSE of 27 mm).…”

Section: A Comparison Of Ztds To the Era5 Datamentioning

confidence: 52%

Development of a New Tabular Zenith Tropospheric Delay Model for Real-Time GNSS Applications

2021

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The tropospheric delay is a major error source for Global Navigation Satellite System (GNSS) positioning and navigation, and usually can be corrected by using an empirical model. Due to the small number of parameters and simplified algorithm, the UNB3m model has been widely hardwired in GNSS receivers for real-time applications. However, many studies have noted that the UNB3m model has significant systematic errors in the correction of tropospheric delays, mainly due to the assumption of north-south symmetry. Therefore, considering the realistic atmospheric behavior, we proposed a new tabular zenith tropospheric delay (TZTD) model using 10 years of NCEP (National Centre for Environmental Prediction) data. The performance of the TZTD model was assessed along with the GPT3 and UNB3m models by comparison with ZTDs derived from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5) data and GNSS observations. The results show that the TZTD model (with a RMSE of 41mm) significantly outperforms the UNB3m model (with a RMSE of 49 mm). Furthermore, the accuracy of the new model is better than that of the GPT3 model in terms of the zenith tropospheric hydrostatic delay (ZHD) prediction, particularly at high altitudes. The TZTD model characterized by simplicity and accuracy, is expected to be a substitute for the UNB3m model in real-time GNSS applications.INDEX TERMS Tropospheric delay model, real-time GNSS applications, numerical weather prediction data, UNB3m, GPT3

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“…al. [27]. At the surface level, the TZTD model have a RMSE of 20 mm which is very close to that of the GPT3 model, and outperforms UNB3m (with a RMSE of 27 mm).…”

Section: A Comparison Of Ztds To the Era5 Datamentioning

confidence: 52%

Development of a New Tabular Zenith Tropospheric Delay Model for Real-Time GNSS Applications

2021

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“…When considering that GNSS plays an important role in atmospheric science and ZTD is important to PPP solutions [31,32,33,34]. It is meaningful to assess the performance of the GPS, BDS-2, BDS-2/BDS-3, GLONASS, Galileo, and multi-GNSS PPP in terms of ZTD accuracy.…”

Section: Data Tests and Results Analysismentioning

confidence: 99%

Assessment of BeiDou-3 and Multi-GNSS Precise Point Positioning Performance

Jiao

Song

et al. 2019

Sensors

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With the launch of BDS-3 and Galileo new satellites, the BeiDou navigation satellite system (BDS) has developed from the regional to global system, and the Galileo constellation will consist of 26 satellites in space. Thus, BDS, GPS, GLONASS, and Galileo all have the capability of global positioning services. It is meaningful to evaluate the ability of global precise point positioning (PPP) of the GPS, BDS, GLONASS, and Galileo. This paper mainly contributes to the assessment of BDS-2, BDS-2/BDS-3, GPS, GLONASS, and Galileo PPP with the observations that were provided by the international Global Navigation Satellite System (GNSS) Monitoring and Assessment System (iGMAS). The Position Dilution of Precision (PDOP) value was utilized to research the global coverage of GPS, BDS-2, BDS-2/BDS-3, GLONASS, and Galileo. In particular, GPS-only, BDS-2-only, BDS-2/BDS-3, GLONASS-only, Galileo-only, and multi-GNSS combined PPP solutions were analyzed to verify the capacity of the PPP performances in terms of positioning accuracy, convergence time, and zenith troposphere delay (ZTD) accuracy. In view of PDOP, the current BDS and Galileo are capable of global coverage. The BDS-2/BDS-3 and Galileo PDOP values are fairly evenly distributed around the world similar to GPS and GLONASS. The root mean square (RMS) of positioning errors for static BDS-2/BDS-3 PPP and Galileo-only PPP are 10.7, 19.5, 20.4 mm, and 6.9, 18.6, 19.6 mm, respectively, in the geographic area of the selected station, which is the same level as GPS and GLONASS. It is worth mentioning that, by adding BDS-3 observations, the positioning accuracy of static BDS PPP is improved by 17.05%, 24.42%, and 35.65%, and the convergence time is reduced by 27.15%, 27.87%, and 35.76% in three coordinate components, respectively. Similar to the static positioning, GPS, BDS-2/BDS-3, GLONASS, and Galileo have the basically same kinematic positioning accuracy. Multi-GNSS PPP significantly improves the positioning performances in both static and kinematic positioning. In terms of ZTD accuracy, the difference between GPS, BDS-2/BDS-3, GLONASS, and Galileo is less than 1 mm, and the BDS-2/BDS-3 improves ZTD accuracy by 20.48% over the BDS-2. The assessment of GPS, BDS-2, BDS-2/BDS-3, GLONASS, Galileo, and multi-GNSS global PPP performance are shown to make comments for the development of multi-GNSS integration, global precise positioning, and the construction of iGMAS.

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“…With the widespread use of GPT series models, many relevant studies have emerged to improve or validate the performance of these models [11][12][13][14][15][16][17][18][19][20][21][22]. However, most validations are conducted at the surface rather than at higher altitudes.…”

Section: Saastamoinen Askne and Nordiusmentioning

confidence: 99%

Development and Assessment of Improved Global Pressure and Temperature Series Models

2021

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Global pressure and temperature (GPT) series models can provide the underlying meteorological parameters for tropospheric corrections without any other meteorological observations, which allows them to be widely used for a series of geodetic as well as meteorological and climatological purposes. Due to the height difference between the empirical model height and user location, a vertical correction of meteorological parameters is inevitable, particularly for airborne users. Unfortunately, the GPT series models have limitations on the vertical correction. We explored the temperature lapse rate for the vertical adjustment using 10 years of reanalysis data provided by the National Centers for Environmental Prediction (NCEP), and extended the GPT models to improved global pressure and temperature (IGPT) series models by introducing a new temperature lapse rate model and a new formulation of pressure reduction. An Evaluation of the IGPT model expression determines that the IGPT models have better accuracy than the GPT models, particularly under large height differences, which is attributed to their ability to consider the real behavior of temperature in the atmosphere and adiabatic effects on air pressure. The performance of the IGPT models in zenith tropospheric delay (ZTD) estimations also has been evaluated by comparison with the fifth-generation European Centers for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5) data and International GNSS Service (IGS) data. The results confirm that our new models can effectively improve the accuracy of ZTDs, particularly at larger altitude differences between the target height and the corresponding four grid points of the model, not only enhancing the performance of the model in complex terrain but also extending the feasibility of IGPT models from the Earth's surface to higher altitudes.

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Establishment and Evaluation of a New Meteorological Observation-Based Grid Model for Estimating Zenith Wet Delay in Ground-Based Global Navigation Satellite System (GNSS)

Cited by 17 publications

References 21 publications

Development of a New Tabular Zenith Tropospheric Delay Model for Real-Time GNSS Applications

Development of a New Tabular Zenith Tropospheric Delay Model for Real-Time GNSS Applications

Assessment of BeiDou-3 and Multi-GNSS Precise Point Positioning Performance

Development and Assessment of Improved Global Pressure and Temperature Series Models

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