USER IMPLEMENTATION AND ASSESSMENT OF BDS-3 PRECISE POINT POSITIONING AUGMENTATION SERVICE WITH NO ECONOMIC COST

The development of GPS station networks that provide rich data sources containing atmospheric information will enable more GPS applications in the field of meteorology. This study describes a genetic algorithm for the water vapour tomography; overcomes the ill-conditioned problem; and eliminates the reliance on excessive constraints, priori information, and external data. It is proven in the paper that accurate 3-D water vapour distribution can be provided by this study for atmospheric research.

In this paper, we propose an improved pixel-based water vapor tomography model, which uses layered optimal polynomial functions by adaptive training for water vapor retrieval. Under different scenarios, tomography results show that the new model outperforms the traditional one by reducing the root-mean-square error (RMSE), and this improvement is more pronounced, at 5.88 % in voxels without the penetration of GNSS rays. The improved model also has advantages in more convenient expression.

A comparison between the GNSS tomography technique and WRFDA in retrieving wet refractivity (WR) is conducted in HK during a wet period and a dry period. The results show that both of them can retrieve good WR. In most of the cases, the WRFDA output outperforms the tomographic WR, but the tomographic WR is better than the WRFDA output in the lower troposphere in the dry period. By assimilating better tomographic WR in the lower troposphere into the WRFDA, we slightly improve the retrieved WR.

This paper proposes an optimal tropospheric tomography approach with the support of an auxiliary area, which has the ability to use the signals crossing out from the top boundary of the tomographic area. Additionally, the top height of the tomography body is determined based on the average water vapour distribution derived from the COSMIC data. The compared result reveals the superiority of the proposed method when compared to the conventional method.