A novel method to integrate IMU and magnetometers in attitude and heading reference systems

Modern attitude and heading reference systems (AHRS) generally use Kalman Filter to integrate gyros with some other augmenting sensors, such as accelerometers and magnetometers, to provide a long term stable orientation solution. The construction of the Kalman Filter for the AHRS is flexible, while the general options are the methods based on quaternion, Euler angles, or Euler angle errors. But the quaternion and Euler angle based methods need model system angular motions; meanwhile all these three methods suffer from nonlinear problems which increase system complexities and computational difficulties. This paper has proposed a novel implementation method for the AHRS integrating IMU and Magnetometer. In the proposed method, the Kalman Filtering is implemented according to the Euler angle errors expressing the local level frame (l frame) errors, rather than the Euler angle errors expressing the body frame (b frame) errors, as the customary methods do. A linear system error model based on the Euler angles errors expressing the l frame errors for the AHRS is developed and the corresponding system observation model is derived. This proposed method for AHRS doesn’t need to model system angular motion and also avoids the nonlinear problem which is inherent in the customarily used methods. The experimental results show that the proposed method is a promising alternative for the AHRS. MSC: 93C95