The recent public release of the PPP-B2b service, along with advancements in
multi-frequency and multi-GNSS systems, has opened up significant new
opportunities for the development of Precise Point Positioning (PPP) technology.
Utilizing the precise orbit and clock corrections provided by PPP-B2b and the
increasing availability of multi-frequency signals, this paper introduces a
novel tri-frequency, dual ionosphere-free PPP model based on PPP-B2b services.
The model is designed with twelve unique tri-frequency combinations, tailored to
various frequency choices, combination methodologies, and single/dual GNSS
systems. Results from static positioning experiments indicate that the BDS-only
tri-frequency dual ionosphere-free model offers substantial improvements over
traditional models. Specifically, it achieves approximately a 25% increase in
vertical accuracy and reduces convergence time by around 30% when compared to
the BDS-only tri-frequency undifferenced uncombined model. This demonstrates the
model's potential to enhance performance under static conditions. For dynamic
positioning, the model proves equally effective. The four BDS-only tri-frequency
dual ionosphere-free combinations show accuracy in the E and U directions
comparable to that of the BDS-only four-frequency undifferenced uncombined
model. However, in the N direction, the tri-frequency dual ionosphere-free
combinations reach an average accuracy of 0.010m, which represents an
approximate 40% improvement over the 0.017m achieved by the four-frequency
undifferenced uncombined model. Additionally, these combinations reduce
convergence time by about 30%.When GPS is incorporated, the dual-system
tri-frequency combination offers even more benefits. Both in dynamic and static
scenarios, the dual-system approach improves convergence time by 20% to 40%
compared to single-system positioning, while also achieving slightly higher
positioning accuracy. These findings underscore the effectiveness of the PPP-B2b
service in optimizing PPP applications for both static and dynamic use
cases.