Research on Dynamic Heading Calculation of Complex Magnetic Disturbance

The rapid development of micro/nano-technology in recent years, an inertial navigation system (INS) composed of MEMS devices is widely used in various fields such as detection, machinery, transportation, and military affairs. The trend of using MEMS devices for navigation in the field of transportation is increasing. The three-dimensional MEMS electronic compass mainly includes a magnetometer and accelerometer. It mainly uses the earth’s magnetic field, gravity acceleration and other parameters to provide the bearing and attitude of the carrier for the navigation system. However, the current inertial navigation system is easy to get lost when it encounters magnetic disturbance, and the irregular movement process is easy to cause errors, even in the static environment is not accurate. In order to solve this problem, in this paper, a dynamic heading filtering algorithm based on Extended Kalman Filter is proposed. The two sets of sensors are used for the positive phase installation, and an extended Kalman filter algorithm is designed. The heading solution can be self-adaption according to different magnetic disturbances. Finally, the experiment verified that the heading error of the carrier after filtering into the dynamic condition was ± 1°, which has met the actual requirements.