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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.

Magnetic azimuth is one of the important parameters of the directional navigation, it provides an important basis for navigation. First, the author deduces the mathematical model of geomagnetic azimuth measurement system, and achieves the full range of measurement of magnetic azimuth through the method of quadrant discriminant. Then, in this paper, it introduces the hardware and software design of the magnetic azimuth measurement system based on the GMR sensor, accelerometer, temperature sensor and microprocessors etc. Finally, this paper gives the actual measurement results of the azimuth measurement system rotated in the horizontal plane. The results show that the system can accurately capture faint magnetic changes, which will meet the requirements of the navigation orientation, and provide a reliable magnetic field data and realize basis for the magnetic azimuth calculation.

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