智能磁航向传感器的研制及误差补偿算法分析

杨新勇; 黄圣国

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智能磁航向传感器的研制及误差补偿算法分析

杨新勇¹,
黄圣国²

1.
南京航空航天大学自动化学院, 南京 210016
2. 南京航空航天大学民航学院, 南京 210016

基金项目: 国家自然科学基金资助项目(79870032)

详细信息

作者简介:
杨新勇(1973-),男,河南郑州人,博士生, yxydoctor@sohu.com.

中图分类号: V 241.611; TP 368.1
计量
- 文章访问数: 2888
- HTML全文浏览量: 179
- PDF下载量: 1623
- 被引次数: 0
出版历程
- 收稿日期: 2002-10-28
- 网络出版日期: 2004-03-31

Development of intelligent magnetic heading sensor and analysis of its error compensation algorithms

Yang Xinyong¹,
Huang Shengguo²

1.
College of Automation Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China
2. College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China

摘要

摘要: 介绍了微型智能磁传感器的设计,分析了影响磁航向精度的误差来源.在此基础上提出了基于BP神经元网络、最小二乘及最佳椭圆拟合等3种不同的磁航向误差补偿算法,详细分析了每种算法的工作原理,并立足于算法的具体实现,通过现场试验,从精度、速度、效率等3个方面对算法的有效性加以分析验证,并得出结论.
- 神经网络 /
- 最小二乘法 /
- 磁阻传感器 /
- 最佳椭圆拟合 /
- 误差补偿
Abstract: The design of a micro intelligent magnetic heading sensor and error sources which affect heading accuracy are introduced. Further, three compensation algorithms based on BP neural networks, least square method and ellipse-specific fitting method are presented respectively. Each compensation algorithm is analyzed in detail. From the point of specific algorithm implementation, accuracy, velocity, efficiency of each compensation algorithm are analyzed and testified based on experimental results.
- neural networks /
- least squares methods /
- magnetic heading sensor /
- ellipse specific fitting method /
- error compensation

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参考文献(1)

[1] Matsuzaki S. Apparatus for estimating current heading using magnetic and angular velocity sensors . U.S. 5235514, 1993 [2]Caruso M. AN-201 implementing a set/reset pulse circuit . http://www.ssec.honeywell.com/magnetic/applications.html, 1999-08-16/2002-09-12 [3]Caruso M J. Application of magneto resistive sensors in navigation systems[J]. Sensors and Actuators, 1997, 42(9):15~21 [4]Fitzgibbon A, Pilu M, Fisher R B. Direct least square fitting of ellipse[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999,21(5):476~480

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