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.