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17 July 2002 Sensor fusion method for off-road vehicle position estimation
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A FOG-aided GPS fusion system was developed for positioning an off-road vehicle, which consists of a six-axis inertial measurement unit (IMU) and a Garmin global positioning system (GPS). An observation-based Kalman filter was designed to integrate the readings from both sensors so that the noise in GPS signal was smoothed out, the redundant information was fused and a high update rate of output signals was obtained. The drift error of FOG was also compensated. By using this system, a low cost GPS can be used to replace expensive GPS with a higher accuracy. Measurement and fusion results showed that the positioning error of the vehicle estimated using this fusion system was greatly reduced from a GPS-only system. At a vehicle speed of about 1.34 m/s, the mean bias in East axis of the fusion system was 0.48 m comparing to the GPS mean bias of 1.28 m, and the mean bias in North axis was reduced to 0.32 m from 1.48 m. The update frequency of the fusion system was increased to 9 Hz from 1 Hz of the GPS. A prototype system was installed on a sprayer for vehicle positioning measurement.
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Linsong Guo, Qin Zhang, and Shufeng Han "Sensor fusion method for off-road vehicle position estimation", Proc. SPIE 4715, Unmanned Ground Vehicle Technology IV, (17 July 2002);

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