Study On The Correction Of Troposphere Based On The VPS Reference Station Network Of Different Regions

Compared with the traditional RTK, VRS technology has lots of advantages, such as widely coverage, lower cost, higher precision and reliability, so the VRS technology is widely used by surveyors. The core technology of VRS is to modify a variety of spatial correlation models which are concerned with positioning. Since the dispersion effect of the ionosphere, ionosphere delay can be well eliminated. As to base station troposphere delay, due to there is no dispersion effect, it usually use model correction results as the initial value, then use observation equations with suitable estimation methods to get end corrections, and use interpolation or fitting methods to modify virtual stations.The paper mainly introduces the principle of VRS, correction methods of ionosphere delay error and satellite orbit error, besides it discusses the troposphere correction models of base station and creation methods of virtual station’s troposphere model. What’s more, it describes the researching results of zenith delay models of troposphere, mapping functions, and interpolation and fitting methods of troposphere in virtual station.1, As to troposphere zenith delay model, in the paper it uses five domestic IGS stations’ meteorological data do computation, analyze the situations of these models Saastamoinen, Hopfiled, EGNOS, UNB3 respectively in the 5 cites, besides analyzes the annual bias of the two models EGNOS and UNBS with unrealistic measured data.2, With regard to the mapping functions, the paper calculates the annual static mapping functions and wet mapping function curves with 2014 data the five IGS stations. The results prove its whole deviation and insensitivity to longitude of NMF, GMF and VMF1 are superior compared to NMF. Furthermore it also verifies the climate discrepancy of LHAZ, located in Tibet Plateau.3, Select part base stations of Hong Kong VRS network to simulate the troposphere, which is similarity with most cities’ CORS. And the paper uses interpolation and fitting respectively to do tests with the data, in the end it can get the conclusions, LCM can get the highest interpolation precision, and LIM has higher extrapolation precision.4, In the case of fitting functions, it tests the influence of elevation is much larger than plane position difference in small area, and thus H1QX1 is the most suitable fitting function.5 This paper shows an improved H1QX1 method. which joined the factor variable error and used whole LSM to previous model, and it has been proved meaningfully.