基于模糊神经网络的地图匹配算法  

Map matching algorithm based on fuzzy neural networks

作　　者：苏海滨[1] 王光政[1] 王继东[1] 

机构地区：[1]华北水利水电学院电力学院,郑州450011

出　　处：《北京科技大学学报》2012年第1期43-47,共5页Journal of University of Science and Technology Beijing

基　　金：华北水利水电学院高层次人才科研启动金资助项目(20101285)

摘　　要：提出了基于模糊神经网络的新的地图匹配算法.该算法综合了数字道路信息和GPS/DR定位信息,提取两个重要参数作为输入变量,即定位点到候选路段的投影距离及定位航向与候选路段方位角差.设计出了四层模糊神经网络及改进的收敛学习规则.实验结果表明所提出的算法能很好地匹配车辆行驶路段位置.A novel map matching method based on fuzzy neural networks was proposed. This method integrates digital road map information and GPS/DR position data, and two important variables, the projection distance from the positioning point to the candidate link and the angle difference between GPS/DR heading and the link bearing of the candidate link, are selected as input signals for fuzzy neural networks. A four-layer fuzzy neural network was designed and the improved learning rule was acquired for the fuzzy neural network. Experimental results show that the proposed algorithm has very good performance for matching the position of car running to the correct link under normal traffic conditions.

关 键 词：车辆 导航系统 全球定位系统 地图匹配 模糊神经网络 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]