多系统融合单点定位先验和验后定权研究

针对多模全球卫星导航系统(GNSS)融合伪距单点定位随机模型难以精确构建的问题，在全球范围内选取了10个多GNSS实验跟踪网MGEX(Multi-GNSS Experiment)观测站连续7天的观测数据，将四大GNSS系统的观测值分为五类，比较了高度角模型、用户等效测距误差(UERE)模型及验后Helmert方差分量估计模型的伪距单点定位精度. 结果表明:在四系统融合伪距单点定位时，Helmert方差分量估计模型能提高定位精度，高度角模型定位精度优于UERE模型，其中基于高度角的Helmert方差分量估计模型结果最优. 

Research on a priori and posterior weighting methods for Multi-GNSS combined single point positioning

When using multi-system code observations to conduct the pseudo range single point positioning, a reasonable stochastic model needs to be determined. In this paper, the datasets from ten multi-system stations MGEX(Multi-GNSS Experiment) on seven consecutive days are selected to compare the positioning performance of pseudo range single point positioning with the elevation-dependent model and the user equivalent range error (UERE) model, as well as the posterior Helmert variance component estimation model based on the two a priori models. The observations from the four Global Navigation Satellite Systems (GNSS) are divided into five groups. The results show that the positioning accuracy can be improved when adopting the Helmert variance component estimation model. The positioning accuracy of the elevation-dependent model is better than that of the UERE model. The Helmert variance component estimation model based on the elevation-dependent weighting strategy achieves the best positioning performance.