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Volume 30 Issue 03
Mar.  2004
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Journal of Beijing University of Aeronautics and Astronautics  > 2004  >  30(03): 244-248.
Yang Xinyong, Huang Shengguo. Development of intelligent magnetic heading sensor and analysis of its error compensation algorithms[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(03): 244-248. (in Chinese)
Citation: Yang Xinyong, Huang Shengguo. Development of intelligent magnetic heading sensor and analysis of its error compensation algorithms[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(03): 244-248. (in Chinese)
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Development of intelligent magnetic heading sensor and analysis of its error compensation algorithms

  • 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

  • Received Date: 28 Oct 2002
  • Publish Date: 31 Mar 2004
    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.

     

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    • References(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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