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http://dx.doi.org/10.5369/JSST.2017.26.4.286

Magnetic Disturbance Model-Embedded Heading Estimation Filter for Time-Varying Magnetic Environments  

Lee, Jung Keun (Department of Mechanical Engineering, Hankyong National University)
Choi, Mi Jin (Department of Mechanical Engineering, Hankyong National University)
Publication Information
Journal of Sensor Science and Technology / v.26, no.4, 2017 , pp. 286-291 More about this Journal
Abstract
With regards to heading estimation using gyroscope and magnetometer signals, magnetic disturbance added in the magnetometer signals is a main degradation factor in the estimation accuracy. Although there are a number of existing mechanisms that may properly compensate for the magnetic disturbances, they are designed to react only to the magnetic disturbances, but not to the time derivative of disturbances. Note that the sensors may experience abrupt changes in the magnetic disturbances, particularly for ambulatory applications. This paper proposes a magnetic disturbance model-embedded heading estimation filter for time-varying magnetic environments. The proposed magnetic disturbance model is based on a first-order Markov chain with a conditional switching technique depending on the time derivative of disturbances. Once a high amount of derivative is detected, the corrupted magnetometer signals are discarded to protect the filter from them. In our experimental results, the averaged heading error of tests was $1.46^{\circ}$, while that of the original approach without switching was $5.75^{\circ}$.
Keywords
Magnetic disturbance model; Heading estimation; Time-varying magnetic environment; Kalman filter;
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Times Cited By KSCI : 2  (Citation Analysis)
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