A novel geomagnetic measurement calibration algorithm based on neural networks

The studying of the geomagnetic field is a fundamental task in geomagnetism navigation and observation. But the magnetometer measurements are usually susceptible to the environmental magnetic field as well as the carrier magnetic field. Therefore a calibration method to the magnetic disturbance is of great significance in practical high-precision measurements. This paper conducts in-depth analysis about the magnetic interference in geomagnetic measurements, and then concerning the characteristics of the magnetic interference, designs and sets up a calibration algorithm based on the BP neural network algorithm. This algorithm can be effective to identify the dynamic characteristics and non-linear problems about the system, and obtain the mapping relationship of the input - output function, with a strong adaptive ability, a high rate of accuracy-time and an effective calibration result.