Research Papers
Multi-sensor data fusion for land vehicle attitude estimation using a fuzzy expert system
Authors:
Jau-Hsiung Wang ,
Department of Geomatics Engineering, The University of Calgary, 2500 University Drive NW, Calgary,
Alberta, Canada T2N 1N4, CA
Yang Gao
Department of Geomatics Engineering, The University of Calgary, 2500 University Drive NW, Calgary,
Alberta, Canada T2N 1N4, CA
Abstract
In Inertial Navigation Systems (INS), the attitude estimated from gyro measurements by the Kalman filter is subject to an unbound error growth during the stand-alone mode, especially for land vehicle applications using low-cost sensors. To improve the attitude estimation of a land vehicle, this paper applies a fuzzy expert system to assist in multi-sensor data fusion from MEMS accelerometers, MEMS gyroscopes and a digital compass based on their complementary motion detection characteristics. Field test results have shown that drift-free and smooth attitude estimation can be achieved and will lead to a significant performance improvement for velocity and position estimation.
How to Cite:
Wang, J.-H. & Gao, Y., (2006). Multi-sensor data fusion for land vehicle attitude estimation using a fuzzy expert system. Data Science Journal. 4, pp.127–139. DOI: http://doi.org/10.2481/dsj.4.127
Published on 05 Jan 2006.
Peer Reviewed
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