| 磁浮列车测速定位中的信息融合研究 |
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| 引用本文： | 李晓龙,刘锡良,史黎明.磁浮列车测速定位中的信息融合研究[J].电子科技大学学报（自然科学版）,2013,42(1):87-91. |
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| 作者姓名： | 李晓龙 刘锡良 史黎明 |
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| 作者单位： | 1.同济大学铁道与城市轨道交通研究院 上海 杨浦区 201804; |
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| 基金项目： | 国家科技支撑计划(2009BAG11B02) |
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| 摘 要： | 将信息滤波融合理论引入中低速磁浮列车测速定位领域, 在交叉感应回线的测速定位基础上增加雷达测速定位传感器和查询应答器, 以交叉感应回线和雷达传感器实现相对定位, 以查询应答器实现绝对定位, 从而得到多传感器信息融合测速定位, 可以显著提高中低速磁浮列车测速定位的精度和可靠性. 最后采用MATLAB仿真对结论进行了验证.
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| 关 键 词： | 信息融合 卡尔曼滤波 测速定位 联邦卡尔曼滤波器 |
| 收稿时间： | 2012-06-13 |
Information Fusion Research in Maglev Train Velocity and Position Detection |
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| Affiliation: | 1.Research Institute of Railway and Mass Transit of Tongji University Yangpu Shanghai 201804;2.Institute of Electrical Engineering,Chinese Academy of Sciences Haidian Beijing 100190 |
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| Abstract: | In this paper, information filtering fusion theory is introducted into the field of low-speed maglev train speed and position detection. Beside the cross induction coil, radar speed sensors and balise are also adopted. The relative positioning is realized by the radar and cross induction coil, and the absolute positioning is realized by the balise. The information fusion comes true by this way. The accuracy and reliability of speed and position detection can be significantly improved. The final conclusion is verified by MATLAB simulation. |
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| Keywords: | information fusion Kalman filter speed and position detection the federal Kalman filter |
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