By Topic

Error Calibration of Magnetometer Using Nonlinear Integrated Filter Model With Inertial Sensors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Wonmo Koo ; Dept. of Aerosp. Inf. Eng., Konkuk Univ., Seoul ; Sangkyung Sung ; Young Jae Lee

This paper presents an onboard heading estimation algorithm using IMU and strapdown magnetometer without other external heading references. To calibrate the magnetic deviation, sensor errors caused by hard iron effect and initial heading of strapdown magnetometers are considered. In our approach, sensor output distortion due to the soft iron effect is ignored, which is relatively small. First, for the estimation of heading angle, system and measurement model is presented. Then particle filter and extended Kalman filter is introduced for performance comparison. The proposed algorithm for the integration of IMU and magnetometer is verified via numerical simulation using Matlab. Simulation result demonstrates accurate heading estimation error under 1 degree for both algorithms when there exists a small initial heading error and hard iron effect, yet particle filter provides more robust and accurate result than the extended Kalman filter in case the initial heading error and biases are large.

Published in:

IEEE Transactions on Magnetics  (Volume:45 ,  Issue: 6 )