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The Global Navigation Satellite System (GNSS) can be utilized for long-distance and high-precision time transmission. With the ongoing development of low Earth orbit (LEO) satellites and the rapidly changing geometric relationships between them, the convergence rate of ambiguity parameters in Precise Point Positioning (PPP) algorithms has increased, enabling fast and reliable time transfer. In this paper, GPS is used as an experimental case, the LEO satellite constellation is designed, and simulated LEO observation data are generated. Then, using the GPS observation data provided by IGS, a LEO-enhanced PPP model is established. The LEO-augmented PPP model is employed to facilitate faster and more reliable high-precision time transfer. The application of the LEO-augmented PPP model to time transfer is examined and discussed through experimental examples. These examples show multiple types of time transfer links, and the experimental outcomes are uniform. GPS + LEO is compared with exclusive GPS time transfer schemes. The clock offset of the time transfer link for the GPS + LEO scheme converges more swiftly, meaning that the time required for the clock offset to reach a stable level is the briefest. In this paper, standard deviation is employed to assess stability, and Allan deviation is utilized to assess frequency stability. The results show that the clock offset stability and frequency stability achieved by the GPS + LEO scheme are superior within the convergence time range. Controlled experiments with different numbers of satellites for LEO enhancement indicate that time transfer performance can be improved by increasing the number of satellites. As a result, augmenting GPS tracking data with LEO observations enhances the time transfer service compared to GPS alone. [ABSTRACT FROM AUTHOR]

A frequency transfer model that is suitable for short baseline links is proposed herein. Based on a GPS single-differenced (SD) observation among two stations, the initial values and the corresponding variance of the SD ambiguity can be estimated. This can form the double-differenced (DD) ambiguity while defining the reference satellite, and can be fixed to an integer value by using the integer search method. After defining the values of the SD ambiguity datum for the reference satellite, the other SD ambiguities can be recovered; then, the final time difference of the two stations can be estimated using the known and fixed SD ambiguities. Validations performed using five different baseline links show that the new method has better accuracy and stability for precise time transfer than the traditional precise point positioning method, and it can be operated in conjunction with the broadcast ephemeris data, which is more convenient for real-time application. [ABSTRACT FROM AUTHOR]

The high precision positioning can be easily achieved by using real-time kinematic (RTK) and precise point positioning (PPP) or their augmented techniques, such as network RTK (NRTK) and PPP-RTK, even if they also have their own shortfalls. A reference station and datalink are required for RTK or NRTK. Though the PPP technique can provide high accuracy position data, it needs an initialisation time of 10–30 min. The time-relative positioning method estimates the difference between positions at two epochs by means of a single receiver, which can overcome these issues within short period to some degree. The positioning error significantly increases for long-period precise positioning as consequence of the variation of various errors in GNSS (Global Navigation Satellite System) measurements over time. Furthermore, the accuracy of traditional time-relative positioning is very sensitive to the initial positioning error. In order to overcome these issues, an improved time-relative positioning algorithm is proposed in this paper. The improved time-relative positioning method employs PPP model to estimate the parameters of current epoch including position vector, float ionosphere-free (IF) ambiguities, so that these estimated float IF ambiguities are used as a constraint of the base epoch. Thus, the position of the base epoch can be estimated by means of a robust Kalman filter, so that the position of the current epoch with reference to the base epoch can be obtained by differencing the position vectors between the base epoch and the current one. The numerical results obtained during static and dynamic tests show that the proposed positioning algorithm can achieve a positioning accuracy of a few centimetres in one hour. As expected, the positioning accuracy is highly improved by combining GPS, BeiDou and Galileo as a consequence of a higher amount of used satellites and a more uniform geometrical distribution of the satellites themselves. Furthermore, the positioning accuracy achieved by using the positioning algorithm here described is not affected by the initial positioning error, because there is no approximation similar to that of the traditional time-relative positioning. The improved time-relative positioning method can be used to provide long-period high precision positioning by using a single dual-frequency (L1/L2) satellite receiver. [ABSTRACT FROM AUTHOR]

• There are two different error sources: one relates to the error propagation law and the other to the systematic bias of the interpolation model. • We verify the existence of systematic errors in the interpolation model. • We discuss the spatial changes in systemic errors of the interpolation model. • A algorithm for estimating the stochastic model of atmospheric corrections is proposed. Regional Augmented Precise Point Positioning (RA-PPP) is a method used to support PPP-Real Time Kinematic (PPP-RTK) based on state space representation. In case of RA-PPP, uncalibrated phase delays and undifferenced ionospheric and tropospheric corrections generated by the reference station network are interpolated at the rover in real time. This study proposes a set of algorithms for estimating the uncertainties of atmospheric corrections that are compatible for use with the RA-PPP model. There are two different error sources of interpolated atmospheric corrections: one relates to the error propagation law and the other to the systematic bias of the interpolation model. We discuss the spatial changes in systemic errors of the interpolation model and present a new interpolation method and its use in calculating the uncertainties of interpolated atmospheric corrections. In addition, we verify the existence of systematic errors in the interpolation model and discuss the correlation between zenith tropospheric delay and slant ionospheric corrections. The results of PPP ambiguity resolution experiments using GPS/Galileo observations are presented. For a reference station network with an interstation distance of more than 110 km, when the proposed method is used, the rate of successfully fixing ambiguities reaches 67.8% in 5 min, and the fixing rate is higher than 90%. It is considered that our method has enhanced applicability for use with large networks and in complex environments. [ABSTRACT FROM AUTHOR]