Comparison on Real-time Single Point Positioning Performance of Single Beidou/Multi-mode GNSS in Remote Forested Areas
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摘要: 在偏远林区, 参考站比较稀疏且较难进行网络通信, 多路径效应大, 观测时卫星周跳数大, 难以利用双差方式进行高精度实时(Real-Time Kinematic, RTK)定位. 为此, 在考虑广播星历钟差引入码硬件延迟的基础上, 推导了单北斗(BDS)/多模全球导航卫星系统(Global Navigation Satellite System, GNSS)单频和消电离层组合的伪距单点定位(Single Point Positioning, SPP)模型, 根据系统钟差基准不同引起的伪距硬件延迟的改正方法, 并采用林区实测的车载动态观测数据进行精度评估, 得出目前卫星导航基于单频SPP和IF SPP在偏远林区可以达到的定位精度. 结果表明, 在林区无参考站改正数的情况下, 单北斗以及GPS/Galileo/ BDS组合的SPP定位平面精度可以达到2 m. 相比单频SPP, 单北斗、GPS/Galileo/BDS消电离层组合SPP的平面精度分别提高约0.5 m和0.4 m, 基于消电离层组合的SPP具有更优的定位性能.Abstract: In remote forested areas, reference stations are sparse, making network communication difficult. There are significant multipath effects, causing large cycle slips during observations, making it challenging to achieve high-precision RTK (Real-Time Kinematic) positioning using double-difference methods. Considering the hardware delay introduced by broadcast ephemeris and clock errors, a pseudorange Single-Point Positioning (SPP) model for single Beidou (BDS)/multi-mode Global Navigation Satellite System (GNSS) single-frequency and ionosphere-free combinations is derived. Correction methods for pseudorange hardware delays caused by different system clock error references is introduced. Accuracy is evaluated using measured vehicle dynamic observation data in forested areas, and the achievable positioning accuracy of current satellite navigation is determined based on single-frequency SPP and ionosphere-free SPP in remote forested regions. The results show that under the condition of no correction data from reference stations in the forest area, the plane accuracy of BDS and GPS/Galileo/BDS SPP positioning can reach 2 m. Compared with single-frequency SPP, the plane accuracy of Beidou, GPS/Galileo/BDS ionosphere-free SPP is improved by about 0.5 m and 0.4 m respectively, and the SPP based on the ionosphere-free combination has better positioning performance.
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表 1 四个模型在三个方向上的定位误差
Table 1. Positioning errors of four models in three directions
Root mean square error / m 模型 East North Up Horizontal BDS单频SPP 1.0 1.9 3.9 2.1 BDS IFSPP 1.4 0.9 4.5 1.6 三系统单频SPP
三系统IF SPP0.5
0.91.5
0.92.6
2.41.6
1.2 -
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