• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus 收录
  • 全国中文核心期刊
  • 中国科技论文统计源期刊
  • 中国科学引文数据库来源期刊

基于数据融合技术的铁路轨道捷联惯性测试方法

王雪梅,  倪文波

downloadPDF
文章导航 > 西南交通大学学报  > 2014 >  27(1): 8-14,51.
王雪梅, 倪文波. 基于数据融合技术的铁路轨道捷联惯性测试方法[J]. 西南交通大学学报, 2014, 27(1): 8-14,51. doi: 10.3969/j.issn.0258-2724.2014.01.002
引用本文: 王雪梅, 倪文波. 基于数据融合技术的铁路轨道捷联惯性测试方法[J]. 西南交通大学学报, 2014, 27(1): 8-14,51. doi: 10.3969/j.issn.0258-2724.2014.01.002
shu
WANG Xuemei, NI Wenbo. Strapdown Inertial Measurement Method Based on Data Fusion Technique and Its Application to Railway Track[J]. Journal of Southwest Jiaotong University, 2014, 27(1): 8-14,51. doi: 10.3969/j.issn.0258-2724.2014.01.002
Citation: WANG Xuemei, NI Wenbo. Strapdown Inertial Measurement Method Based on Data Fusion Technique and Its Application to Railway Track[J]. Journal of Southwest Jiaotong University, 2014, 27(1): 8-14,51. doi: 10.3969/j.issn.0258-2724.2014.01.002
shu

基于数据融合技术的铁路轨道捷联惯性测试方法

doi: 10.3969/j.issn.0258-2724.2014.01.002
基金项目: 

中央高校基本科研业务费专项资金资助项目（SWJTU11CX021）

Strapdown Inertial Measurement Method Based on Data Fusion Technique and Its Application to Railway Track

    摘要
  • 摘要: 为了进一步提高捷联惯性测试系统的精度，提出了基于卡尔曼数据融合技术的铁路轨道几何参数捷联惯性测试方法.在分析影响捷联惯性测试系统精度主要误差因素的基础上，建立了反映测试系统误差影响因素的状态空间方程，分析了外部辅助观测量的选取及其对卡尔曼滤波系统可观测性和可观测度的影响.以速度、侧滚角作为外部辅助观测量，并且以2阶自回归模型对随机振动干扰进行实时建模，仿真计算结果表明，相较于普通的卡尔曼滤波算法，该方法可以使卡尔曼滤波的估计精度显著提高，俯仰角和航向角误差估计值的标准偏差均减小1.5°~2.5°.

     

    Abstract: To further increase the accuracy of strapdown inertial measurement system, based on Kalman data fusion technique, a novel strapdown inertial measuring method for railway track geometrical parameters was proposed. By analyzing major error factors that affect the strapdown inertial system, the error state space equations were constructed. The selection of external observations and their influences on the observability and the degree of observability of the Kalman filter were also analyzed. The velocity and roll angle were used as external observations, and the random vibration interference was modeled with second-order auto-regression equations. The simulation results show that compared with the common Kalman filtering algorithm, the proposed method can greatly increase the estimation accuracy of Kalman filtering state variables, and the standard deviation of pitch angle and azimuth angle is decreased by 1.5° to 2.5°.

     

    • HTML全文
    • 参考文献(16)
  • 王雪梅, 倪文波. 铁路轨道几何参数捷联惯性测量基准建立[J]. 西南交通大学学报, 2012, 47(3): 355-360. WANG Xuemei, NI Wenbo. Datum plane foundation of railway track geometrical parameters measurement based on strapdown inertial technique[J]. Journal of Southwest Jiaotong University, 2012, 47(3): 355-360.
    钟晓春, 张海涛, 姜向东, 等. 基于SINS/GPS的高速列车组合导航系统[J]. 西南交通大学学报, 2010, 45(4): 580-584. ZHONG Xiaochun, ZHANG Haitao, JIANG Xiangdong, et al. SINS/GPS integrated navigation system for high-speed trains[J]. Journal of Southwest Jiaotong University, 2010, 45(4): 580-584.
    侯卫星, 刘刚, 康熊. 0号高速综合检测列车[M]. 北京:中国铁道出版社, 2010: 40-45.
    卞鸿巍, 李安, 覃方君. 现代信息融合技术在组合导航中的应用[M]. 北京:国防工业出版社, 2010: 1-39.
    SAHAWNEH L R, Al-JARRAH M A, ASSALEH K, et al. Real-time implementation of GPS aided low-cost strapdown inertial navigation system[J]. Journal of Intelligent Robot System, 2011(61): 527-544.
    蔡体菁, 刘莹, 宋军, 等. 嵌入式GPS/MIMU/磁罗盘组合导航系统[J].仪器仪表学报, 2010, 31(12): 2695-2699. CAI Tijing, LIU Ying, SONG Jun, et al. Embedded integrated GPS/MIMU/compass navigation system[J]. Chinese Journal of Scientific Instrument, 2010, 31(12): 2695-2699.
    张慧君, 廖炳瑜, 袁洪. 基于强跟踪滤波器的MIMU/GPS组合导航系统[J]. 计算机仿真, 2011, 28(4): 62-65. ZHANG Huijun, LIAO Bingyu, YUAN Hong. MIMU/GPS integrated navigation system based on strong tracking filter[J]. Journal of Computer Simulation, 2011, 28(4): 62-65.
    刘春, 周发根. 机载捷联惯导的导航计算模型与精度分析[J]. 同济大学学报:自然科学版, 2011, 39(12): 1865-1870. LIU Chun, ZHOU Fagen. Navigation calculation model for airborne SINS and its accuracy analysis[J]. Journal of Tongji University: Natural Science, 2011, 39(12): 1865-1870.
    付旭, 周兆英. MEMS自动驾驶仪中的多传感器误差补偿[J]. 清华大学学报:自然科学版, 2008, 48(5): 804-807. FU Xu, ZHOU Zhaoying. Error compensation with multiple sensors in a MEMS autopilot[J]. Journal of Tsinghua University: Science & Technology, 2008, 48(5): 804-807.
    何子述, 夏威. 现代数字信号处理及其应用[M]. 北京:清华大学出版社, 2009: 244-286.
    章燕申. 高精度导航系统[M]. 北京:中国宇航出版社, 2005: 45-69.
    戴维德 H T, 约翰 L W. 捷联惯性导航技术[M]. 2版. 张天光, 王秀萍, 王丽霞, 译. 北京:国防工业出版社, 2007: 263-294.
    秦永元. 惯性导航[M]. 北京:科学出版社, 2006: 287-390.
    万德均, 房建成. 惯性导航初始对准[M]. 南京:东南大学出版社, 1998: 83-106.
    GOSHEN-MESKIN D, BAR-ITZHACK I Y. Observability analysis of piece-wise constant systems-part Ⅰ: theory[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(4): 1056-1067.
    GOSHEN-MESKIN D, BAR-ITZHACK I Y. Observability analysis of piece-wise constant systems-part Ⅱ: application to inertial navigation in-flight alignment[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(4): 1068-1075.
    • 相关文章
    • 施引文献
  • 附加材料(0)
  • 加载中
WeChat 点击查看大图
计量
  • 文章访问数:  1059
  • HTML全文浏览量:  74
  • PDF下载量:  679
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-04-10
  • 刊出日期:  2014-01-25

目录

    /

    返回文章
    返回

    Copyright © 2009 西南交通大学学报

    地址：四川省成都市郫都区犀安路999号西南交通大学犀浦校区《西南交通大学学报》编辑部

    电话：028-66367562传真：028-66366552Email：xbz@home.swjtu.edu.cn

    本系统由 北京仁和汇智信息技术有限公司 开发 技术支持： info@rhhz.net