In-flight Heading Estimation of Strapdown Magnetometers using Particle Filters

This paper presents a real-time heading estimation algorithm using IMU and strapdown magnetometer without any other external heading reference. To calibrate the magnetic deviation, sensor errors caused by hard iron effect and initial heading of strapdown magnetometers are considered. In our approach...

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Bibliographic Details
Published in2008 IEEE National Aerospace and Electronics Conference pp. 379 - 384
Main Authors Wonmo Koo, Sebum Chun, Sangkyung Sung, Young Jae Lee, Taesam Kang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Distortion measurement
Goniometers
Iron
Magnetic sensors
Magnetic separation
Magnetometers
Mathematical model
Nonlinear distortion
Numerical simulation
Particle filters
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Summary:This paper presents a real-time heading estimation algorithm using IMU and strapdown magnetometer without any other external heading reference. 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 derived, which is nonlinear. 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 in Matlab. Simulation result demonstrates accurate heading estimation error within 1 degree for both algorithms when there exists small initial heading error and hard iron effect, yet particle filter provides more robust and precise result than the extended Kalman filter in case the initial heading error and biases are large.
ISBN:1424426154
9781424426157
ISSN:0547-3578
2379-2027
DOI:10.1109/NAECON.2008.4806576