A heading correction technology based on magnetometer calibration and adaptive anti-interference algorithm

Magnetic and inertial measurement units are extensively used to determine the navigation systems' attitude and position. However, magnetic sensors are susceptible to external ambient disturbance, which leads to heading estimation errors. This paper establishes a unified error correction model for the magnetometer to improve the accuracy and reliability of the measurement results. After applying the algorithmic correction, the root mean square error (RMSE) of the magnetic field data is significantly reduced by 91.70%, reaching a value of only 0.85uT. Additionally, an adaptive heading correction algorithm is proposed to suppress magnetic interference. It introduces a generalized likelihood ratio test (GLRT) method to detect magnetic interference. GLRT is suitable for inference problems in the case of small sample data, and the sensitivity and specificity of magnetic anomaly detection can be adjusted by setting thresholds to adapt to different application requirements and environmental conditions. When there is magnetic interference, this correction algorithm dynamically adjusts the weight of magnetic sensor data through GLRT. The experimental results show that the proposed algorithm can reduce the directional error by 91.20% in the magnetic interference environment. It is expected to find applications in various fields, including military navigation, aviation, and aerospace.

Automated summary

This paper proposes a unified error correction model for magnetometers and an adaptive heading correction algorithm to improve the accuracy and reliability of measurement results. Experimental results show that the algorithm can significantly reduce directional error in the presence of magnetic interference.