Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia

This paper first analyses the precision of tropospheric zenith total delay (ZTD) values obtained from the empirical models GPT2 and GPT2w, and the numerical weather models (NWM) from Australian Bureau of Meteorology (BoM), and European Centre for Medium-Range Weather Forecasts (ECMWF). Comparison of these ZTD values with IGS ZTD product at four sites showed that the ZTDs from NWM datasets were more precise than the empirical models. The ZTD from BoM data gave the best results, with mean errors between -0.034 m to 0.029 m and standard deviations better than 0.045 m. Next, the PPP convergence time and achievable accuracy using the BoM NWM constrained ZTD by including them as pseudo-observations with a pre-set precision was compared to the case of estimating the troposphere. This resulted in a slight enhancement in convergence time, and improvements in vertical positioning accuracy was found at all the four tested sites at 0.036–0.058 m after 2 min, 0.023–0.038 m after 3 min and 0.013–0.020 m after 5 min of PPP initialisation

EXAMINATION OF DIFFERENT MODELS OF TROPOSPHERE DELAYS IN SBAS POSITIONING IN AERIAL NAVIGATION

This paper presents the results of a study on the use of different tropospheric correction models in SBAS positioning for air navigation. The paper, in particular, determines the influence of the Saastamoinen troposphere and RTCA-MOPS models on the determination of aircraft coordinates and mean coordinate errors in the SBAS positioning method. The study uses real kinematic data from a GPS navigation system recorded by an onboard GNSS satellite receiver as well as SBAS corrections. In the experiment, the authors include SBAS corrections from EGNOS and SDCM augmentation systems. The navigation calculations were performed using RTKLIB v.2.4.3 and Scilab 6.1.1 software. Based on the conducted research, it was found that the difference in aircraft coordinates using different troposphere models can reach up to ±2.14 m. Furthermore, the use of the RTCA-MOPS troposphere model improved the values of mean coordinate errors from 5 to 9% for the GPS+EGNOS solution and from 7 to 12% for the GPS+SDCM solution, respectively. The obtained computational findings confirm the validity of using the RTCA-MOPS troposphere model for SBAS positioning in aerial navigation

Assessment of Three Tropospheric Delay Models (IGGtrop, EGNOS and UNB3m) Based on Precise Point Positioning in the Chinese Region

Tropospheric delays are one of the main sources of errors in the Global Navigation Satellite System (GNSS). They are usually corrected by using tropospheric delay models, which makes the accuracy of the models rather critical for accurate positioning. To provide references for suitable models to be chosen for GNSS users in China, we conduct herein a comprehensive study of the performances of the IGGtrop, EGNOS and UNB3m models in China. Firstly, we assess the models using 5 years’ Global Positioning System (GPS) derived Zenith Tropospheric Delay (ZTD) series from 25 stations of the Crustal Movement Observation Network of China (CMONOC). Then we study the effects of the models on satellite positioning by using various Precise Point Positioning (PPP) cases with different tropospheric delay resolutions, the observation data processed in PPP is from 21 base stations of CMONOC for a whole year of 2012. The results show that: (1) the Root Mean Square (RMS) of the IGGtrop model is about 4.4 cm, which improves the accuracy of ZTD estimations by about 24% for EGNOS and 19% for UNB3m; (2) The positioning error in the vertical component of the PPP solution obtained by using the IGGtrop model is about 15.0 cm, which is about 30% and 21% smaller than those of the EGNOS and UNB3m models, respectively. In summary, the IGGtrop model achieves the best performance among the three models in the Chinese region