The models and algorithms of uncombined precise point positioning with BDS/GLONASS data

On the basis of the GPS uncombined precise point positioning (PPP) model, new suitable models for BDS and GLONASS uncombined PPP are proposed respectively, considering the different characteristics of BDS and GLONASS. And based on this, the function model for joint BDS/GLONASS processing is constructed. In this new model, systematical code biases caused by long-period multipath effects of BDS GEO satellites are considered and estimated as parameters. Additionally, GLONASS code inter-frequency-biases (IFB) are taken into consideration and modeled as a linear function of frequency numbers. A full-rank function model and estimable parameters are obtained through a re-parameterization process. To validate the correctness and effectiveness of the new model, one month of data from DOY (day of year) 200-300, 2015 of 11 MGEX stations are processed. Results show that parameterizing code BGMB (BDS GEO Multipath Bias) can improve convergence speed significantly and reduce code residuals in the BDS uncombined PPP. Besides, the linear function model for GLONASS code IFB can also improve convergence speed dramatically and reduce code residuals to some extent in the GLONASS PPP. RMS of the joint BDS/GLONASS positioning errors using one month of data are 6. 9 mm, 9. 1 mm and 19. 3 mm, for north, east and up components respectively, which indicates that the proposed joint BDS/GLONASS uncombined PPP models and algorithms have good positioning performance.