摘要
针对在城市峡谷、树木茂盛、隧道等环境下进行全球卫星导航系统(GNSS)动态测量,容易因卫星数量不足而造成常规的最小二乘定位算法无法完成定位解算的问题,对现有的4种GNSS数据缺失定位算法进行比较分析:介绍4种算法的基本原理,并分析其在实际应用中的优缺点;然后使用实测数据对4种算法的性能进行评估。结果表明:在3颗观测卫星的情况下,伪距预报算法在3个方向上的精度都要优于其他3种算法;当观测卫星数少于3颗时,伪距预报和卡尔曼(Kalman)滤波算法的定位精度均会随可见卫星数的减少而降低,但伪距预报算法的定位精度始终优于Kalman滤波算法。
Aiming at the problem that it is difficult to implement positioning solution for conventional least square positioning algorithm under the environment of urban canyons,dense trees,tunnels and so on in kinematic GNSS surveying,the paper comparatively analyzed the existing four GNSS positioning algorithms with inadequate satellite data:the principles of the algorithms were introduced,and the advantages and disadvantages of them in practical application were analyzed,then their performance were evaluated by measures.Result showed that:the pseudorange prediction algorithm would be superior to the other algorithms in three directions under the case of 3 visible satellites;and when the number of observed satellites is less than 3,the accuracy of pseudorange prediction and Kalman filtering algorithms would both decrease with the decrease of the number of visible satellites,while the positioning accuracy of pseudorange prediction algorithm would be always better than that of Kalman filtering algorithm.
作者
王勋
崔先强
高天杭
WANG Xun;CUI Xianqiang;GAO Tianhang(School of Geosciences and Information Physics,Central South University,Changsha 410083,China)
出处
《导航定位学报》
CSCD
2020年第2期43-48,共6页
Journal of Navigation and Positioning
基金
国家自然科学基金项目(41674012)。
关键词
动态全球卫星导航系统
城市峡谷
伪距预报
卡尔曼滤波
可靠性
kinematic global navigation satellite system(GNSS)
urban canyon
pseudorange prediction
Kalman filtering
reliability
