Real-Time Tractor Position Estimation System Using a Kalman Filter

A real time tractor position estimation system, which consists of a six axis inertial measurement unit (IMU) and a Garmin global positioning system (GPS) was developed. A Kalman filter was designed to integrate the signals from both sensors so that the noise in GPS signal was smoothed out, the redundant information fused and a high update rate of output signals obtained. The drift error of IMU was also compensated. By using this system, a low cost GPS can be used to replace expensive one with a high accuracy. Test and fusion results showed that the positioning error of the tractor estimated using this system was greatly reduced from a GPS only system. At a tractor speed of about 1.34 m/s, the mean bias in easting axis of the system was 0.48 m, comparing to the GPS mean bias of 1.28 m, and the mean bias in northing axis was reduced from 1.48 m to 0.32 m. The update frequency of the GPS system was increased from 1 to 9 Hz.