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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
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Yang Gao

Department of Geomatics Engineering, The University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada T2N 1N4, CA
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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.
DOI: http://doi.org/10.2481/dsj.4.127
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
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Published on 05 Jan 2006.
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