摘要
基于城市环境下采集的多系统GNSS数据研究非监督分类算法和图优化(factor graph optimization,FGO)算法对多路径误差的抑制能力。伪距单点定位(single point positioning,SPP)结果表明,基于K-means++的非监督分类算法进行多路径信号分离时,在N、E、U方向的定位精度分别为3.61 m、2.90 m、8.14 m,较传统算法分别提升53.18%、55.18%、44.96%。图优化方法利用伪距和多普勒约束因子进行最优估计,在N、E、U方向的定位精度分别为0.94 m、1.34 m、2.78 m,精度分别提升82.1%、78.5%、82.0%。图优化算法对城市环境下GNSS定位的多路径误差抑制具有显著效果,可用于GNSS精密定位预处理阶段的异常卫星剔除和精确坐标初值获取,提高城市环境下GNSS定位性能。
Based on the GNSS data collected in the urban environment,we evaluate the performance of the unsupervised classification algorithm and the graph optimization algorithm to reduce the multipath errors.The results show that the accuracy of SPP can reach 3.61 m,2.90 m and 8.14 m in the N,E and U directions based on the K-means++unsupervised classification algorithm;53.18%,55.18%and 44.96%improvements are observed compared to the traditional algorithm.The graph optimization method making use of the pseudorange and doppler factors can achieve an accuracy of 0.94 m,1.34 m and 2.78 m in the N,E and U directions,with the improvements of 82.1%,78.5%and 82.0%compared to the traditional method.The graph optimization algorithm is proven to decrease the multipath errors in GNSS positioning under urban environments,which can be used to eliminate the abnormal satellites and provide precise initial coordinates for precise positioning,improving the performance of GNSS positioning in urban environments.
作者
丁杨
赵乐文
李飞翔
DING Yang;ZHAO Lewen;LI Feixiang(School of Remote Sensing and Geomatics Engineering,Nanjing University of Information Science and Technology,219 Ningliu Road,Nanjing 210044,China;Jiangsu Engineering Center for Collaborative Navigation/Positioning and Smart Applications,219 Ningliu Road,Nanjing 210044,China;Technology Innovation Center of Integration Applications in Remote Sensing and Navigation,Ministry of Natural Resources,219 Ningliu Road,Nanjing 210044,China)
出处
《大地测量与地球动力学》
CSCD
北大核心
2023年第10期1015-1019,1031,共6页
Journal of Geodesy and Geodynamics
基金
国家自然科学基金(42104018)
中国博士后科学基金(2022M711669)。
关键词
非监督分类
图优化
伪距单点定位
多路径误差
unsupervised classification
factor graph optimization
SPP
multipath errors
