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