摘要
深入研究了各向异性磁阻(AMR)传感器的数据采集原理及特征波形向量提取方法,提出基于AMR传感器及加权欧氏距离的车辆分类识别算法。道路车辆检测实验数据显示,与感应线圈车辆检测法及视频车辆检测等方法相比,该检测方法基本不受环境路况天气等外在因素的影响,满足长期稳定精确等车辆检测的要求,同时在性能、成本、寿命、实时性、维护和升级等方面整体上有较大的优越性。
Based on the research of the anisotropic magnetoresistive（AMR） sensor data acquisition,and characteristics of the wave vector extraction method,this paper presented an AMR sensors and weighted Euclidean distance based vehicle classification and recognition algorithm.Road vehicle detection experimental results indicate that this method is almost not affected by road environment and weather factors comparing to inductive loop and vision-based vehicle detection methods.It also meets the long-term stable and accurate vehicles detection requirements,while performance,cost,life circle real-time,maintenance and upgrading,etc.are superior to the traditional detection methods.
出处
《计算机应用研究》
CSCD
北大核心
2010年第7期2533-2535,2555,共4页
Application Research of Computers
基金
武汉市科学技术局关键技术攻关项目(20061002078)
关键词
智能交通
车型分类
磁阻传感器
加权欧氏距离
地磁测量
ITS
vehicle classification
AMR sensor
weighted Euclidean distance
magnetic field measurement
