As an important component of atmosphere, water vapor is highly involved in the global water cycle and energy exchange. To date, Global Navigation Satellite System (GNSS) and radiosonde techniques have been widely used to detect the water vapor content in the atmosphere. Recently, European Centre for Medium‐Range Weather Forecasts (ECMWF) has released the latest reanalysis data set, namely, ECMWF Re‐Analysis (ERA5), whose temporal and spatial resolutions have a significant improvement over its previous‐generation product of ERA‐Interim. This study aims to assess the consistency of precipitable water vapors (PWVs) derived from ERA5, ERA‐Interim, GNSS, and radiosondes during the entire year of 2017. The GNSS‐derived PWVs were obtained at 41 Crustal Movement Observation Network of China stations, while the radiosonde‐derived PWVs were acquired at the adjacent 41 radiosonde stations. The nationwide PWVs derived from the ERA5 and ERA‐Interim show root‐mean‐square (RMS) errors of 1.8 and 2.1 mm with respect to the GNSS PWVs and 2.7 and 2.8 mm with respect to the radiosonde PWVs, respectively. Besides, the RMS errors exhibit significant regional and seasonal differences. The nationwide relative RMS of the ERA5‐ and ERA‐Interim‐derived PWVs are 11.1% and 13.4% with respect to the GNSS PWVs and 16.2% and 17.8% with respect to the radiosonde PWVs, respectively. The relative RMS values show significant difference between the east and west sides of Hu line across China. Furthermore, the nationwide PWVs are obtained using GNSS data sets at over 200 Crustal Movement Observation Network of China stations to compare with the ERA5‐derived PWVs in China. Results indicate that the spatial distribution of the PWVs derived from the two data sources is quite consistent, suggesting a great application prospect of the ERA5 products in China.

The single point positioning (SPP) mode has been widely used in many fields such as vehicle navigation, Geographic Information System and land surveying. For a long period, the SPP technology mainly relies on GPS system. With the recent revitalisation of the GLONASS constellation and two newly emerging constellations of BeiDou and Galileo, it is now feasible to investigate the performance of quad-constellation integrated SPP (QISPP) with GPS, GLONASS, BeiDou and Galileo measurements. As a satellite-based positioning technology, the QISPP is expected to improve the accuracy and availability of positioning solutions due to the increased number of visible satellites and the improved satellite sky distribution. In this study, a QISPP model is presented to simultaneously process observations from all four Global Navigation Satellite System (GNSS) constellations. Datasets collected at 47 globally distributed Multi-GNSS Experiment (MGEX) stations on two consecutive days and a kinematic experimental dataset are employed to fully assess the QISPP performance in terms of positioning accuracy and availability. Given that most navigation users are using single-frequency receivers, only the observations on a single frequency are utilised. The results indicate that the QISPP improves the positioning accuracy by an average of 16, 13 and 12% using the MGEX datasets, and 43, 31 and 51% using the kinematic experimental dataset over the GPS-only case in the east, north and up components, respectively. The availability of the QISPP solutions remains 100% even for a mask elevation angle of 40°, whereas it is only 37% for the GPS-only case. All these results are achieved using geodetic-type receivers and they are possibly optimistic for users who use navigation-type receivers.

The single-frequency precise point positioning (PPP) technique has attracted increasing attention due to its high accuracy and low cost. However, a very long convergence time, normally a few hours, is required in order to achieve a positioning accuracy level of a few centimeters. In this study, an approach is proposed to accelerate the single-frequency PPP convergence by combining quad-constellation global navigation satellite system (GNSS) and global ionospheric map (GIM) data. In this proposed approach, the GPS, GLONASS, BeiDou, and Galileo observations are directly used in an uncombined observation model and as a result the ionospheric and hardware delay (IHD) can be estimated together as a single unknown parameter. The IHD values acquired from the GIM product and the multi-GNSS differential code bias (DCB) product are then utilized as pseudo-observables of the IHD parameter in the observation model. A time varying weight scheme has also been proposed for the pseudo-observables to gradually decrease its contribution to the position solutions during the convergence period. To evaluate the proposed approach, datasets from twelve Multi-GNSS Experiment (MGEX) stations on seven consecutive days are processed and analyzed. The numerical results indicate that the single-frequency PPP with quad-constellation GNSS and GIM data are able to reduce the convergence time by 56%, 47%, 41% in the east, north, and up directions compared to the GPS-only single-frequency PPP.

The near-real-time high spatial resolution of atmospheric water vapor distribution is vital in numerical weather prediction. GPS tomography technique has been proved effectively for three-dimensional water vapor reconstruction. In this study, the tomography processing is optimized in a few aspects by the aid of radiosonde and COSMIC historical data. Firstly, regional tropospheric zenith hydrostatic delay (ZHD) models are improved and thus the zenith wet delay (ZWD) can be obtained at a higher accuracy. Secondly, the regional conversion factor of converting the ZWD to the precipitable water vapor (PWV) is refined. Next, we develop a new method for dividing the tomography grid with an uneven voxel height and a varied water vapor layer top. Finally, we propose a Gaussian exponential vertical interpolation method which can better reflect the vertical variation characteristic of water vapor. GPS datasets collected in Hong Kong in February 2014 are employed to evaluate the optimized tomographic method by contrast with the conventional method. The radiosonde-derived and COSMIC-derived water vapor densities are utilized as references to evaluate the tomographic results. Using radiosonde products as references, the test results obtained from our optimized method indicate that the water vapor density accuracy is improved by 15 and 12 % compared to those derived from the conventional method below the height of 3.75 km and above the height of 3.75 km, respectively. Using the COSMIC products as references, the results indicate that the water vapor density accuracy is improved by 15 and 19 % below 3.75 km and above 3.75 km, respectively.

Precise point positioning (PPP) technology is mostly implemented with an ambiguity-float solution. Its performance may be further improved by performing ambiguity-fixed resolution. Currently, the PPP integer ambiguity resolutions (IARs) are mainly based on GPS-only measurements. The integration of GPS and GLONASS can speed up the convergence and increase the accuracy of float ambiguity estimates, which contributes to enhancing the success rate and reliability of fixing ambiguities. This paper presents an approach of combined GPS/GLONASS PPP with fixed GPS ambiguities (GGPPP-FGA) in which GPS ambiguities are fixed into integers, while all GLONASS ambiguities are kept as float values. An improved minimum constellation method (MCM) is proposed to enhance the efficiency of GPS ambiguity fixing. Datasets from 20 globally distributed stations on two consecutive days are employed to investigate the performance of the GGPPP-FGA, including the positioning accuracy, convergence time and the time to first fix (TTFF). All datasets are processed for a time span of three hours in three scenarios, i.e., the GPS ambiguity-float solution, the GPS ambiguity-fixed resolution and the GGPPP-FGA resolution. The results indicate that the performance of the GPS ambiguity-fixed resolutions is significantly better than that of the GPS ambiguity-float solutions. In addition, the GGPPP-FGA improves the positioning accuracy by 38%, 25% and 44% and reduces the convergence time by 36%, 36% and 29% in the east, north and up coordinate components over the GPS-only ambiguity-fixed resolutions, respectively. Moreover, the TTFF is reduced by 27% after adding GLONASS observations. Wilcoxon rank sum tests and chi-square two-sample tests are made to examine the significance of the improvement on the positioning accuracy, convergence time and TTFF.

High-rise buildings are susceptible to wind-induced displacements, which can be precisely monitored by using GPS technology. However, GPS monitoring applications may be subject to signal interference and high hardware costs. This study presents a new wind-induced vibration monitoring approach that is based on the mixed use of high-rate and low-rate GPS receivers. In the proposed approach, high-rate receivers are only required in the monitoring stations, where we apply time-differenced positioning to obtain position changes between adjacent epochs. The derived high-rate monitoring station position changes are then integrated with low-rate single epoch relative positioning results between the monitoring and reference stations. Experimental results with both simulated and real data show that the proposed method has a comparable performance with the traditional relative positioning approach, in terms of determining buildings’ vibration frequency, displacement, and acceleration.