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Attitude Tracking based on Sequential Geomagnetic Observations

In the conventional approaches, in order to compensate the gyroscope accumulative error of the low-cost inertial sensor, the positioning system on the hand wearing equipment mostly is using the joint estimation of gravity and magnetic direction to calibrate the tracking attitude (such as Magdwick Filter). However, in the moving state, due to the complicated movement of human arms, the accuracy of using the gravity direction as a reference for the tracking estimation in this scene will decrease. In the outdoor scene, the magnetic field can be used as a reliable observation. In this paper, we use a multi-state constrained Kalman filter to jointly estimate the real values of the sensor attitude and magnetic field in the global frame in real time with the magnetic field observation of the sequence attitude. This method eliminates the dependence of attitude estimation on gravity and reduces the error caused by insufficient observation of single magnetic field. Compared with the traditional method, the proposed method has considerable accuracy and higher robustness in complex motion scenes.