Performance Compensation of GMR-based Magnetic Azimuth Measurement System

摘要：

The magnetic azimuth is one of the important parameters of the directional navigation. This paper proposes a magnetic azimuth measurement system based on the GMR sensor. With the thoughts of information fusion, we study the performance compensation method of magnetic azimuth measurement system based on the radial basis function (RBF) neural network and the BP neural network, and then establish a coupling disturbance compensation model of the magnetic field and the temperature. The experimental results illustrate that the maximum full-scale error of sensor output without compensation is ±21.3％, and the maximum full-scale error after the coupling compensation of the BP neural network and the RBF neural network are ±2.72％ and ±0.52％ respectively.

关键词： GMR Sensor Magnetic Azimuth RBF Neural Networks Coupling Compensation

作者: Xueli Zheng Jingqi Fu

作者单位: School of Mechanical and Electrical Engineering and Automation, Shanghai University, Shanghai 200072, China

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 3285-3288

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）