| Tropospheric delay is a major error source which affects the initialization and re-initialization speed of the GNSS medium-/long-range baseline in Network RTK positioning.Traditional tropospheric delay correction models are not easy to meet the requirements of GNSS high-precision measurement,fusing the meteorological data from NWP model to estimate tropospheric delay is one of the current research hotspots.At present,General Regression Neural Network(GRNN)has been applied in many fields.GRNN has a high learning speed and simple structure,it can approximate any function with arbitrary precision,and has broad prospects for fitting tropospheric delay problems.In this study,we develop a regional NWP tropospheric delay inverstion method based on a GRNN model to improve the accuracy of the tropospheric delay derived from the NWP model.This paper focuses on the methods of the tropospheric delay correction by using NWP model,the research work carried out and the results are as follows:(1)The influence of tropospheric delay error in GNSS positioning is introduced.The accuracy of ZTD estimation between NWP model and two classical tropospheric delay correction models is compared,and the results show that the accuracy of NWP estimation ZTD is higher.(2)Based on the high-precision tropospheric products of 100 IGS stations around the world,the accuracy of ZTD is analyzed by two commonly used NWP model meteorological data(ECMWF reanalysis data and NCEP reanalysis data).The experimental results show that the accuracy of ZTD is higher with ECMWF reanalysis data.(3)The variation law of residual estimated by using the EMWWF data with latitude,temperature,humidity and season is analyzed.It is found that the residual of ZTD estimated by using NWP model is most affected by temperature and relative humidity.(4)A new regional NWP tropospheric delay correction model based on GRNN is proposed.The tropospheric delay is modeled based on NCAR tropospheric data and ECMWF reanalysis data of 650 stations in Japan.The results show that the average residual and RMSD of the ZTD estimated by using the new method are 9.5 mm and 12.7 mm,respectively,which is 20.8%and 19.1%higher than the standard NWP estimated ZTD,respectively. |
