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This paper presents a real-time calibration algorithm for tri-axial magnetometer. A non-linear state space model for calibration related parameters is derived by the invariance norm of local geomagnetic field, and cubature Kalman filter (CKF) is used to estimate calibrating parameters in sequential manner, which is more suitable for real-time critical applications. The effectiveness of the algorithm are verified by numerical simulations. The results are compared with the traditional TWO-STEP algorithm, and the corresponding conclusions are obtained.

Through the causation analysis of divergent solution in determining the magnetic sphere parameters with normal least square method, the result indicates that redundant parameters, especially the angle parameters, are the main factor to cause divergence in non‐linear equations. Therefore, an approach was proposed here to eliminate the influence of angle parameters by regarding magnetic anomaly components as observed value and substituting magnetic moment vector for magnetic inclination as well as magnetic declination. Based on the linear/non‐linear relationship between observed value and magnetic moment/center position, the geometry and physical parameters of magnetic sources could be precisely figured out by applying two‐step iterative least square approach. Considering the influence of background field and multi‐sources situation, corresponding data processing methods were also put forward. The effectiveness of the suggested techniques has been illustrated by real magnetic data from a collection of environmental ferro‐metallic objects. The conclusion shows that the presented approach is convergent and the calculated geometry together with physical parameters has very high precision

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