Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 17; pp. 4705 - 4715
• Main Authors: Ge, Haibo, Meng, Guanlong, Li, Bofeng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Chebyshev approximation; Clocks; Data interruption; Earth orbit; Earth orbits; Errors; Global navigation satellite system; Global Positioning System; Kinematics; low earth orbit (LEO) satellites; Low earth orbit satellites; Low earth orbits; Mechanical components; Navigation; Navigational satellites; Orbit determination; Orbits; precise point positioning (PPP) reconvergence; Real time; real-time kinematic orbit determination; Real-time systems; Satellite observation; Satellite orbits; Satellites
• ISSN: 1939-1404; 2151-1535
• DOI: 10.1109/JSTARS.2024.3362395

With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root-mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%-80% in other two components.