摘要
针对现有地图匹配方法难以同时保障匹配准确率和效率的问题,笔者提出一种基于地图信息建立观测方程的地图匹配方法。首先,根据车载全球卫星导航系统(GNSS)设备的定位精度设置缓冲区确定候选路段;其次,根据距离、方向及路网邻接关系确定候选路匹配度;再次,采用卡尔曼滤波方法融合地图信息与GNSS观测信息;最后,确定路段最佳匹配道路。实验结果表明,该方法在复杂的城市路网下具有良好的匹配效果,证明了笔者提出的地图匹配方法的有效性与可靠性。
Aiming at the problem that the existing map matching methods are difficult to guarantee the matching accuracy and efficiency at the same time,this paper proposes a map matching method to establish observation equations based on the map information.Firstly,according to the positioning accuracy of vehicle Global Navigation Satellite System(GNSS)equipment,the buffer zone is set to determine the candidate road segment.Secondly,the candidate road matching degree was determined according to the distance,direction and road network adjacency relationship.Then,the Kalman filter method was used to fuse map information and GNSS observation information,and finally,the best matching road section was determined.Experimental results show that the proposed method has a good matching effect in the complex urban road network,which proves the effectiveness and reliability of the proposed map matching method.
作者
李明新
黄劲松
LI Mingxin;HUANG Jingsong(School of Geodesy and Geomatics Wuhan University,Wuhan 430079,China)
出处
《导航定位学报》
CSCD
2022年第5期128-134,共7页
Journal of Navigation and Positioning
关键词
地图匹配
卡尔曼滤波
观测方程
全球卫星导航系统
匹配度
map matching
Kalman filter
observation equation
global navigation satellite system
matching score
