摘要
分析了现有常用测速定位方法的不足及缺陷,从联邦卡尔曼滤波原理出发,提出了基于多源信息融合的磁浮列车组合式测速定位方法。该方法有效整合了惯性导航系统、全球卫星导航系统以及多普勒雷达传感器,成功搭建了列车运动模型,并设计、改良了融合算法。基于MATLAB软件仿真平台进行仿真试验,验证了该方法的有效性和可靠性。
The shortcomings and defects of the existing positioning and speed measuring methods are analyzed.Based on federated Kalman filter principle,a maglev train integrated positioning and speed measuring method based on multi-source information fusion is proposed.This method effectively integrates Inertial Navigation System,GNSS(global navigation satellite system)and Doppler radar sensor.A train movement model is successfully built,and the fusion algorithm is designed and optimized.Based on the simulation tests on MATLAB software simulation platform,the effectiveness and reliability of the proposed method is verified.
作者
成庶
刘畅
宋丽伟
向超群
李林
CHENG Shu;LIU Chang;SONG Liwei;XIANG Chaoqun;LI Lin(School of Transportation Engineering,Central South University,410075,Changsha,China;不详)
出处
《城市轨道交通研究》
北大核心
2022年第8期136-140,共5页
Urban Mass Transit
基金
国家重点研发计划项目(2016YFB1200601)
磁浮交通车辆系统集成湖南省重点实验室课题(2018TP1035)。
关键词
磁浮列车
测速定位
信息融合
卡尔曼滤波
maglev
positioning and speed measuring
information fusion
Kalman filter
