The time of a satellite navigation system is primarily generated by the main control station of the ground system. Consequently, when ground stations fail, there is a risk to the continuous provision of time services to the equipment and users. Furthermore, the anticipated launch of additional satellites will further strain the satellite–ground link. Next-generation satellite navigation systems will rely on time deviation measurements from inter-satellite links to independently establish and maintain a space-based time reference, enhancing the system’s reliability and robustness. The increasing number of low-Earth-orbit satellite navigation constellations provides ample resources for establishing a space-based time reference. However, this also introduces challenges, including extensive time scale computations, increased link noise, and low clock resource utilization. To address these issues, this paper proposes a Distributed Kalman Plus Weight (D-KPW) algorithm, which combines the benefits of Kalman filtering and the weighted average algorithm, balancing the performance with computational resources. Furthermore, an adaptive clock control algorithm, D-KPW (Control), is developed to account for both the short-term and long-term frequency stability of the time reference. The experimental results demonstrate that the frequency stability of the time reference established by the D-KPW (Control) algorithm reaches $7.40\times {10}^{-15}$ and $2.30\times {10}^{-15}$ for sampling intervals of 1000 s and 1,000,000 s, respectively, outperforming traditional algorithms such as ALGOS. The 20-day prediction error of the time reference is 1.55 ns. Compared to traditional algorithms such as AT1, ALGOS, Kalman, and D-KPW, the accuracy improves by 65%, 65%, 66%, and 67%, respectively.

Global Navigation Satellite System (GNSS)-based time synchronization is widely used in national critical infrastructure due to its low cost, high precision, and all-weather capability. Real-time precise point positioning (RT-PPP), which corrects satellite orbits and clock offsets via real-time service (RTS), is an effective approach for high-precision time synchronization. However, GNSS signals are vulnerable to natural electromagnetic interference and deliberate attacks, leading to time synchronization failures. Current timing devices suffer from limited monitoring capability and poor interconnection. To address this issue, this paper proposes a system-level monitoring method based on a dynamic graph model, which makes full use of inter-station redundant information by jointly monitoring the clock offsets of multiple stations obtained via RT-PPP. The experimental results show that in the scenario of small timing anomalies, the proposed method achieves an area under the curve (AUC) of 0.94, which is significantly better than the 0.87 and 0.90 achieved by two traditional single station monitoring algorithms, indicating that the method has more sensitive detection performance.