Contribution analysis of QZSS to single-frequency PPP of GPS/BDS/GLONASS/Galileo
Contribution analysis of QZSS to single-frequency PPP of GPS/BDS/GLONASS/Galileo
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QZSS对GPS/BDS/GLONASS/Galileo单频PPP的贡献分析
DOI：
10.1016/j.asr.2020.01.003
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发表时间：
2020-04-01
影响因子：
2.6
通讯作者：
Han, Junqiang
中科院分区：
文献类型：
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作者：
Hong, Ju;Tu, Rui;Han, Junqiang
日本宇宙航空研究开发机构建立的准天顶卫星系统（QZSS）主要服务于亚太地区及其周边地区。目前，有四颗在轨卫星提供服务。大众市场上大多数GNSS用户由于成本低而使用单频（SF）接收机。因此，随着GNSS和QZSS的出现，分析和评估QZSS对GPS/BDS/GLONASS/Galileo系统的SF精确点定位（PPP）的贡献具有重要意义。本文比较了群与相位电离层校正（GRAPHIC）模型、带编码观测的GRAPHIC模型和电离层约束模型三种SF PPP模型的性能，评估了QZSS对GPS/BDS/GLONASS/Galileo系统SF PPP的贡献。此外，还分析了码偏对北斗系统顺波购买力平价的影响。选取MGEX网络10个站点的两周数据集（DOY 013-026, 2019）进行验证，结果表明：(1)截断仰角为15度、20度和25度时，GLONASS + QZSS的静态SF PPP收敛时间分别降低4.3%、30.8%和12.7%，定位精度与GLONASS系统相当。与BDS单一系统相比，BDS QZSS在15度和25度下的静态SF PPP收敛次数分别降低了37.6%和39.2%，水平定位精度分别提高了18.6%和14.1%，垂直定位精度分别提高了13.9%和21.4%。在截断仰角为15度、20度和25度时，GPS/BDS/GLONASS/Galileo + QZSS的定位精度和精度与GPS/BDS/GLONASS/Galileo相似。在截断仰角为20°和25°时，收敛次数分别减少了7.4%和4.3%。在模拟动态PPP时，QZSS显著提高了BDS和GLONASS的定位精度。然而，QZSS对GPS-only、Galileo-only和GPS/BDS/GLONASS/Galileo系统的影响很小。(2)北斗IGSO和MEG的码偏在SF PPP中不容忽视。在静态SF PPP中，以多径组合最大的B1I频段为例，垂直分量的系统偏差约为0.4-1.0 m。修正码偏后，垂直分量的定位误差小于0.2 m，水平分量的定位精度相应提高。(3)带电离层约束的SF PPP模型收敛速度更快，三种模型的定位精度基本相等。因此，在没有外部电离层产品的情况下，GRAPHIC模型可以获得较好的定位精度，但其收敛速度较慢。(c) 2020年比价。Elsevier Ltd.出版。版权所有。
The Quasi-Zenith Satellite System (QZSS) established by the Japan Aerospace Exploration Agency mainly serves the Asia-Pacific region and its surrounding areas. Currently, four in-orbit satellites provide services. Most users of GNSS in the mass market use single-frequency (SF) receivers owing to the low cost. Therefore, it is meaningful to analyze and evaluate the contribution of the QZSS to SF precise point positioning (PPP) of GPS/BDS/GLONASS/Galileo systems with the emergence of GNSS and QZSS. This study compares the performances of three SF PPP models, namely the GRoup and PHase Ionospheric Correction (GRAPHIC) model, GRAPHIC with code observation model, and an ionosphere-constrained model, and evaluated the contribution of the QZSS to the SF PPP of GPS/BDS/GLONASS/Galileo systems. Moreover, the influence of code bias on the SF PPP of the BDS system is also analyzed. A two-week dataset (DOY 013-026, 2019) from 10 stations of the MGEX network is selected for validation, and the results show that: (1) For cut-off elevation angles of 15, 20, and 25 degrees, the convergence times for the static SF PPP of GLONASS + QZSS are reduced by 4.3, 30.8, and 12.7%, respectively, and the positioning accuracy is similar compared with that of the GLONASS system. Compared with the BDS single system, the convergence times for the static SF PPP of BDS QZSS under 15 and 25 degrees are reduced by 37.6 and 39.2%, the horizontal positioning accuracies are improved by 18.6 and 14.1%, and the vertical components are improved by 13.9 and 21.4%, respectively. At cut-off elevation angles of 15, 20, and 25 degrees, the positioning accuracy and precision of GPS/BDS/GLONASS/Galileo + QZSS is similar to that of GPS/BDS/GLONASS/Galileo. And the convergence times are reduced by 7.4 and 4.3% at cut-off elevation angles of 20 and 25 degrees, respectively. In imitating dynamic PPP, the QZSS significantly improves the positioning accuracy of BDS and GLONASS. However, QZSS has little effect on the GPS-only, Galileo-only and GPS/BDS/GLONASS/Galileo. (2) The code bias of BDS IGSO and MEG cannot be ignored in SF PPP. In static SF PPP, taking the frequency band of B1I whose multipath combination is the largest among the frequency bands as an example, the vertical component has a systematic bias of approximately 0.4-1.0 m. After correcting the code bias, the positioning error in the vertical component is lower than 0.2 m, and the positioning accuracy in the horizontal component are improved accordingly. (3) The SF PPP model with ionosphere constraints has a better convergence speed, while the positioning accuracy of the three models is nearly equal. Therefore the GRAPHIC model can be used to get good positioning accuracy in the absence of external ionosphere products, but its convergence speed is slower. (C) 2020 COSPAR. Published by Elsevier Ltd. All rights reserved.