Analysis And Calibration Of Three-axis Fluxgate Magnetometers Error

Three-axis fluxgate magnetometers are widely used in vector measurement of magnetic field because of many advantages such as small cubage, little weight, simple structure, high sensitivity, little eletricity consumption and convenient operation. Especially, three-axis fluxgate magnetometers are significant in the area of object detecting, geomagnetism navigation and missile navigation. In other words, three-axis fluxgate magnetometers, to some extent, can not be replaced by other sensors in geomagnetism vector measurement. However, there are some kinds of error caused by offset, different scale factor and non-orthogonality, which will directly influence the precision of geomagnetism navigation system and other magnetic measurement systems. So, it is necessary to research reasons of three-axis fluxgate magnetometers error. In addition, it is necessary to investigate the compensation and calibration technology of measured data and it is necessary to solve theoretical and technical problems related to compensation and calibration.In this paper, the error calibration of three-axis fluxgate magnetometers is studied based on experiment equipments and parameter estimation theory. Firstly, the significance of calibration and its research situation are introduced. Secondly, error reasons and influence degree of three-axis fluxgate magnetometers are analysed. Thirdly, diversionary error calibration with linear neural networks based on the first total value calibration model is researched. And the method of combining with equipments and adaptive filter based on the second total value calibration model is researched to calibrate diversionary error. Fourthly, extended kalman filter based on vector calibration model is used to calibrate vector error. Lastly, temperature characteristic of the fluxgate magnetometer is tested and the method of temperature error compensation is researched.Research results are introduced as follows: First of all, Influence degree caused by different parameters are researched, and then, the key factor related to diversionary error is concluded. Vector output model is given and the output situation is described when the magnetometer is rotating. Scale factor calibration model are put forward, which describe the way to calibrate scale factor based on equipments. Offset of each axis is calibrated via equipments, and the reliability of calibrated result is validated. Linearity error is analysed, and it is proved that the fluxgate magnetometer is with good performance about linearity. Parameters of three-axis fluxgate magnetometers are estimated by linear neural networks and diversionary error is reduced. Then, disadvantages of double adaptive filter are overcomed by combining with equipments and adaptive filter based on the second total value calibration model. In disturbing magnetic field circumstance, calibration situation is improved by FIR digital filter. It is worth mentioning that diversionary error is calibrated and convergent calibration weights are obtained when three-axis fluxgate magnetometers is rotated randomly, and it is proved that calibration weights are universal. Furthermore, extended kalman filter based on vector calibration model is used to calibrate vector via simulation. Finally, temperature compensation model established, and the model is proved to be universal.In the end, some conclusions are given and some suggestions for further research are described in detail.