| 利用GPS和惯性传感器的融合和集成实现车辆定位 |
| |
| 引用本文： | 蔡伯根.利用GPS和惯性传感器的融合和集成实现车辆定位[J].北京交通大学学报(自然科学版),2000,24(5):7-14. |
| |
| 作者姓名： | 蔡伯根 |
| |
| 作者单位： | 北方交通大学电子信息工程学院!北京100044 |
| |
| 摘 要： | 首先介绍了常用的车辆定位技术 :全球卫星定位系统 (GPS)和航位推算法 (DR) ,并分析各自的优缺点 ,然后提出用卡尔曼滤波 (KalmanFilter)技术来实现GPS和惯性传感器的融合和集成的组合定位 .最后给出了现场测试的结果 ,证明方法的有效性 .
|
| 关 键 词： | 全球卫星定位系统 卡尔曼滤波 航位推算 多传感器融合 智能交通系统 |
Vehicle Positioning via Fusion and Integration of GPS and Inertial Sensors |
| |
| CAI Bai,gen.Vehicle Positioning via Fusion and Integration of GPS and Inertial Sensors[J].JOURNAL OF BEIJING JIAOTONG UNIVERSITY,2000,24(5):7-14. |
| |
| Authors: | CAI Bai gen |
| |
| Abstract: | In this paper, firstly some common-used vehicle location technologies such as GPS and dead reckoning (DR) are presented. Their advantages and disadvantages are analyzed respectively. Secondly an integrated location system implemented by the integration and fusion of GPS and inertial sensors using Kalman filter is proposed. Finally the field test results are given to verify the effectiveness of the proposed method. |
| |
| Keywords: | GPS Kalman Filter Dead Reckoning(DR) Multi sensor fusion Intelligent Transportation System(ITS) |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
