An improved method for real-time PPP timing and time transfer with broadcast ephemerides
An improved method for real-time PPP timing and time transfer with broadcast ephemerides
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广播星历实时PPP授时与时间传递的改进方法
DOI：
10.1088/1361-6501/ac7c57
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发表时间：
2022-06
影响因子：
2.4
通讯作者：
Xuhai Yang
中科院分区：
文献类型：
--
作者：
Yulong Ge;Xinyun Cao;Feng Zhou;Fei Shen;Fuyang Ke;Xuhai Yang
摘要由于网络通信的问题，实时精密单点定位（PPP）授时/授时的可靠性很难用实时精密产品来保证。随着空间信号测距误差的不断减小，首次在真实的时间中分析了GPS和Galileo PPP定时/时间传递与广播星历的性能和可行性。然后，针对GPS与Galileo PPP系统在真实的时间上的时间传递问题，提出了一种平滑方法和时间序列分解方法来减小噪声和插值误差。结果表明，在当前状态下，GPS或Galileo PPP对时在15 360 s时可以达到4 × 1 × 10 −14的水平。GPS和Galileo PPP的时间传递精度分别为（0.46-0.81）ns和（0.44-0.61）ns。GPS和Galileo PPP在15 360 s时的频率稳定度约为7.0 × 1 × 10 −14和5.0 × 1 × 10 −14。值得注意的是，通过应用我们的方法，GPS和Galileo PPP定时/时间传输的频率稳定性的最大改善高达99%。此外，GPS或Galileo PPP时间传递的平均精度可以达到约0.3 ns，与传统方法相比，提高了高达67.3%。
Abstract Due to the problem of network communication, it is difficult to ensure the reliability of real-time precise point positioning (PPP) timing/time transfer with real-time precise products. With the continued reduction in the signal-in-space range error, the performance and feasibility of GPS and Galileo PPP timing/time transfer with broadcast ephemeris were analyzed for the first time in real time. Then, we present a smoothing method and time-series decomposition method to reduce the noise and the interpolation error for GPS and Galileo PPP timingtime transfer with broadcast ephemeris in real time. The results show that GPS or Galileo PPP timing with broadcast ephemeris can achieve a 4 × 1 × 10 −14 level at 15 360 s in the current state. The accuracy is about (0.46–0.81) ns and (0.44–0.61) ns for GPS and Galileo PPP time transfer. The frequency stability is at about 7.0 × 1 × 10 −14 and 5.0 × 1 × 10 −14 levels at 15 360 s for GPS and Galileo PPP. It is important to note that by applying our approach, the maximum improvement in frequency stability for GPS and Galileo PPP timing/time transfer is up to 99%. Furthermore, the average accuracy of GPS or Galileo PPP time transfer can achieve approximately 0.3 ns, which is an improvement of up to 67.3% compared to the traditional method.
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DOI：
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期刊：
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