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A Novel Method to Integrate IMU and Magnetometers in Attitude and Heading Reference Systems

Published online by Cambridge University Press:  12 September 2011

Songlai Han  and
Jinling Wang
Songlai Han*
Affiliation:
(National University of Defense Technology, China)
Jinling Wang*
Affiliation:
(National University of Defense Technology, China)
*
(Email: [email protected]
(Email: [email protected])
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Abstract

Modern attitude and heading reference systems (AHRS) generally use Kalman filters 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 to model system angular motions, and, meanwhile, all these three methods suffer from nonlinear problems which will increase the system complexities and the computational difficulties. This paper proposes a novel implementation method for the AHRS integrating IMU and magnetometer sensors. In the proposed method, the Kalman filtering is implemented to use the Euler angle errors to express the local level frame (l frame) errors, rather than express 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 has been developed and the corresponding system observation model has been derived. This proposed method for AHRS does not need to model system angular motions and also avoids the nonlinear problem which is inherent in the commonly used methods. The experimental results show that the proposed method is a promising alternative for the AHRS.

Keywords

AHRSKalman filterIMUMagnetometer
Type
Research Article
Information
The Journal of Navigation , Volume 64 , Issue 4 , October 2011 , pp. 727 - 738
Copyright
Copyright © The Royal Institute of Navigation 2011

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