Improvement of MEMS-IMU/GPS performance using fuzzy modeling

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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