Improvement of MEMS-IMU/GPS performance using fuzzy modeling |
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Authors: | W Abdel-Hamid T Abdelazim N El-Sheimy G Lachapelle |
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Institution: | (1) Department of Geomatics Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta, T2N1N4, Canada |
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Abstract: | Performance improvement of integrated Inertial Measurement Units (IMU) utilizing micro-electro-mechanical-sensors (MEMS) and
GPS is described in this paper. An offline pre-defined Fuzzy model is employed to improve the system performance. The Fuzzy
model is used to predict the position and velocity errors, which are the inputs to a Kalman Filter (KF) during GPS signal
outages. The proposed model has been verified on real MEMS inertial data collected in a land vehicle test. A number of 30-s
GPS outages were simulated during the data processing at different times and under different vehicle dynamics. Performance
of the suggested Fuzzy model was compared to that of the traditional KF particularly during the simulated GPS outages. The
test results indicate that the proposed Fuzzy model can efficiently compensate for GPS updates during short outages. |
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Keywords: | MEMS INS/GPS Takagi-Sugeno systems Fuzzy logic modeling Navigation |
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