School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China.
Shanxi Provincial Key Laboratory for Resources, Environment and Disaster Monitoring, Jinzhong 030600, China.
Sensors (Basel). 2019 Jan 21;19(2):417. doi: 10.3390/s19020417.
Reliable and continuous navigation solutions are essential for high-accuracy location-based services. Currently, the real-time kinematic (RTK) based Global Positioning System (GPS) is widely utilized to satisfy such requirements. However, RTK's accuracy and continuity are limited by the insufficient number of the visible satellites and the increasing length of base-lines between reference-stations and rovers. Recently, benefiting from the development of precise point positioning (PPP) and BeiDou satellite navigation systems (BDS), the issues existing in GPS RTK can be mitigated by using GPS and BDS together. However, the visible satellite number of GPS + BDS may decrease in dynamic environments. Therefore, the inertial navigation system (INS) is adopted to bridge GPS + BDS PPP solutions during signal outage periods. Meanwhile, because the quality of BDS geosynchronous Earth orbit (GEO) satellites is much lower than that of inclined geo-synchronous orbit (IGSO) satellites, the predicted observation residual based robust extended Kalman filter (R-EKF) is adopted to adjust the weight of GEO and IGSO data. In this paper, the mathematical model of the R-EKF aided GEO/IGSO/GPS PPP/INS tight integration, which uses the raw observations of GPS + BDS, is presented. Then, the influences of GEO, IGSO, INS, and R-EKF on PPP are evaluated by processing land-borne vehicle data. Results indicate that (1) both GEO and IGSO can provide accuracy improvement on GPS PPP; however, the contribution of IGSO is much more visible than that of GEO; (2) PPP's accuracy and stability can be further improved by using INS; (3) the R-EKF is helpful to adjust the weight of GEO and IGSO in the GEO/IGSO/GPS PPP/INS tight integration and provide significantly higher positioning accuracy.
可靠且连续的导航解决方案对于高精度基于位置的服务至关重要。目前，实时动态（RTK）的全球定位系统（GPS）被广泛用于满足此类需求。然而，RTK 的精度和连续性受到可视卫星数量的限制以及参考站和移动站之间基线长度的增加。最近，得益于精密单点定位（PPP）和北斗卫星导航系统（BDS）的发展，可以通过同时使用 GPS 和 BDS 来缓解 GPS RTK 中存在的问题。然而，GPS+BDS 的可见卫星数量在动态环境中可能会减少。因此，惯性导航系统（INS）被用于在信号中断期间桥接 GPS+BDS PPP 解决方案。同时，由于 BDS 地球同步轨道（GEO）卫星的质量远低于倾斜地球同步轨道（IGSO）卫星，因此采用基于预测观测残差的稳健扩展卡尔曼滤波（R-EKF）来调整 GEO 和 IGSO 数据的权重。在本文中，提出了一种基于 GPS+BDS 原始观测值的 R-EKF 辅助 GEO/IGSO/GPS PPP/INS 紧组合的数学模型。然后，通过处理车载数据评估了 GEO、IGSO、INS 和 R-EKF 对 PPP 的影响。结果表明：（1）GEO 和 IGSO 都可以提高 GPS PPP 的精度，但 IGSO 的贡献比 GEO 更为显著；（2）使用 INS 可以进一步提高 PPP 的精度和稳定性；（3）R-EKF 有助于调整 GEO/IGSO/GPS PPP/INS 紧组合中 GEO 和 IGSO 的权重，提供显著更高的定位精度。
