High-precision Global Navigation Satellite Systems (GNSS) orbits are critical for real-time clock estimation and precise positioning service; however, the prediction error grows gradually with the increasing prediction session. In this study, we present a new efficient precise orbit determination (POD) strategy referred to as the epoch-parallel processing to reduce the orbit update latency, in which a 24-h processing job is split into several sub-sessions that are processed in parallel and then stacked to solve and recover parameters subsequently. With a delicate handling of parameters crossing different sub-sessions, such as ambiguities, the method is rigorously equivalent to the one-session batch solution, but is much more efficient, halving the time-consuming roughly. Together with paralleling other procedures such as orbit integration and using open multi-processing (openMP), the multi-GNSS POD of 120 satellites using 90 stations can be fulfilled within 30 min. The lower update latency enables users to access orbits closer to the estimation part, that is, 30–60-min prediction with a 30-min update latency, which significantly improves the orbit quality. Compared to the hourly updated orbit, the averaged 1D RMS values of predicted orbit in terms of overlap for GPS, GLONASS, Galileo, and BDS MEO are improved by 39%, 35%, 41%, and 37%, respectively, and that of BDS GEO and IGSO satellites is improved by 47%. We also demonstrate that the boundary discontinuities of half-hourly orbit are within 2 cm for the GPS, GLONASS, and Galileo satellites, and for BDS the values are 2.6, 15.5, and 9.8 cm for MEO, GEO, and IGSO satellites, respectively. This method can also be implemented for any batch-based GNSS processing to improve the efficiency.

高精度全球导航卫星系统（GNSS）轨道对于实时时钟估计和精确定位服务至关重要；然而，随着预测会话的增加，预测误差逐渐增大。在本研究中，我们提出了一种新的高效精确轨道确定（POD）策略，称为历元并行处理，以减少轨道更新延迟，其中 24 小时的处理作业被分成几个子会话，这些子会话在并行然后堆叠以随后求解和恢复参数。通过对跨不同子会话的参数（例如歧义性）进行精细处理，该方法严格相当于单会话批处理解决方案，但效率更高，耗时大致减半。与轨道整合和使用开放式多处理（openMP）等并行其他程序一起，可以在 30 分钟内完成使用 90 个站的 120 颗卫星的多 GNSS POD。较低的更新延迟使用户能够访问更接近估计部分的轨道，即30-60分钟的预测和30分钟的更新延迟，从而显着提高轨道质量。与每小时更新的轨道相比，GPS、GLONASS、Galileo、BDS MEO的预测轨道平均一维均方根值分别提高了39%、35%、41%和37%，北斗GEO和IGSO卫星性能提升47%。我们还证明，对于 GPS、GLONASS 和 Galileo 卫星，半小时轨道的边界不连续性在 2 cm 以内；对于 BDS，MEO、GEO 和 IGSO 卫星的值分别为 2.6、15.5 和 9.8 cm。该方法也可以应用于任何基于批处理的 GNSS 处理，以提高效率。