基于GNSS伪距观测值与最小二乘解的卡尔曼滤波模型验证研究  

Verification Research of Kalman Filter Model Based on GNSS Pseudo Range Observations and Least Squares Solution

作　　者：郑海玲 Zheng Hailing(Shanghai Surveying and Mapping Institute)

机构地区：[1]上海市测绘院,上海市200063

出　　处：《勘察科学技术》2021年第6期11-15,共5页Site Investigation Science and Technology

摘　　要：在车载激光扫描应用中,由于车载点云数据精度受GNSS多路径效应、路测场景多样性的影响,因此该文采用基于GNSS伪距观测值和最小二乘解的卡尔曼滤波结果进行实验分析,并通过与城市实测伪距差分数据比较分析两种算法的异同与优劣。结果表明,基于GNSS伪距观测值的滤波模型能充分利用所有观测量,并具有较好的抗多径能力;而基于最小二乘解的模型易于程序实现,同时可避免从复杂场景进入开阔场景时滤波器的异常收敛问题。In the application of vehicle laser scanning,because the accuracy of vehicle point cloud data is affected by GNSS multipath effect and the diversity of road test scenes,therefore,this paper makes the experimental analysis based on the Kalman filter results by the GNSS pseudo range observation value and least square solution,and compares the similarities and differences and the advantages and disadvantages of the two algorithms through the difference data of urban measured pseudo range.The results show that the filtering model based on GNSS pseudo range observations can make full use of all observations,and has good anti multipath ability;The model based on the least square solution is easy to program,and can avoid the abnormal convergence of the filter when entering the open scene from the complex scene.

关 键 词：伪距观测值 最小二乘解 卡尔曼滤波 DGPS 

分 类 号：P228.4[天文地球—大地测量学与测量工程] TN713[天文地球—测绘科学与技术] TN967.1[电子电信—电路与系统]