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《Chinese Journal of Sensors and Actuators》 2008-11
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Neural Network Compensation for Low-Cost Magnetic Heading System in Integrated Navigation

LIU Yu-hao,HUANG Xin-sheng,XU Wan-ying(College of Mechatronics and Automation,National University of Defense Technology,Changsha 410073,China)  
According to the characters of integrated navigation,a neural network is designed to compensate the error of a low-cost magnetic heading system(MHS).The error sources of MHS are studied and the compensation methods are analyzed.When the Global Positioning System(GPS)is available,a multilayer feedforward neural network is designed to compensate MHS with the learning method of Kalman filter and the reference of strapdown inertial navigation system(SINS)/GPS integrated navigation result.Experiment results show that the neural network can make a significant effect and reduce the heading error of MHS from ±15° to ±1°.
【Fund】: 兵器预研基金项目资助(2020203)
【CateGory Index】: TN966;TP183
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