A new residual correction model for ZTD inversion of NWP under multi-factor constraints
YAN Lizi;MA Dan;XU Ying;WANG Shengli;FAN Caoming;College of Geomatics, Shandong University of Science and Technology;Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation,School of Resources and Environment, Fujian Agriculture and Forestry University;Institute of Ocean Engineering, Shandong University of Science and Technology;
Tropospheric delay is one of the main error source in GNSS positioning. Using the meteorological data of NWP model to invert ZTD is the current research hotspot. However, the ZTD residuals inverted by the reanalysis data of the two meteorological forecast centers(ECMWF and NCEP) are generally floating between ±60 mm, and the precision of ZTD inverted by Forecast data would be worse. As a result, both of them are not able to be used directly for precise positioning. The accuracy of ZTD inverted by NWP will directly affect the convergence speed of the troposphere and ambiguity parameters in the filtering process. Previous research shows that the residual size of the ZTD inverted by the NWP is related to the latitude of the station, and the correlation function between latitude and ZTD residual would improve the precision of the ZTD inverted by the NWP, but the effect is not obvious. To solve this issue, researchers usually take this ZTD as an initial value and set a priori variance, and take the residual as a unknown parameter. Immutable and inaccurate prior variance will directly lead to the troposphere and ambiguity parameters of user station converge slowly, even divergence in the filtering process. In view of the above problems, this paper compares the accuracy of ZTD inverted by ECMWF and NCEP reanalysis data, and then analyzes the change law of the residual of ZTD inverted by ECMWF data with temperature, humidity, latitude, season and other factors. On this basis, a new residual correction model for NWP ZTD inversion under multi-factor constraints is proposed in this paper to improve the accuracy of ZTD by NWP inversion. This model fit the ZTD residual using the polynomial fitting based on the least absolute residuals method. It will provide more accurate priori information for NWP ZTD. To verify the performance of this model, the high precision ZTD of 133 IGS stations are taken as reference, and the residual ZTD inverted by 2015 ECMWF are fitted to establish residual correction model. Then this model is applied to correct the ZTD inverted by 2016 ECMWF. Experimental results show that, in higher latitude areas(above 15 °), the yearly residual and RMS error of the ZTD inverted by ECMWF is reduced separately by 86.9% and 36.3% than that before using the dynamic stochastic correction model. In addition, in the lower latitude areas, this residual correction model is not obvious.
【Fund】： 国家自然科学基金项目(41704021);; 山东省自然科学基金项目(ZR2017QD002);; 山东科技大学人才引进科研启动基金项目(2017RCJJ075);山东科技大学研究生科技创新项目(SDKDYC180315);; 青岛市应用基础研究计划项目(18-2-2-42-jch);; 山东省重点研发计划项目(2018GGX109008)
【CateGory Index】： P456.7
【CateGory Index】： P456.7