The use of low-cost single GPS receivers and inertial sensors for auto-guidance applications has been limited by their reduced accuracy and signal drift over time compared to real-time kinematic(RTK)differential GPS u...The use of low-cost single GPS receivers and inertial sensors for auto-guidance applications has been limited by their reduced accuracy and signal drift over time compared to real-time kinematic(RTK)differential GPS units and fiber-optic gyroscope(FOG)sensors.In this study,a prototype low-cost GPS/INS integrated system consisting of a triangle-shaped array of three Garmin 19x GPS receivers and an Xsens inertial measurement unit(IMU)to improve the accuracy of position and heading angle measured with a single GPS receiver was developed.A triangular algorithm that uses data collected from the three single GPSs mounted on the angular points of a triangular frame was designed.A sensor fusion algorithm based on the Kalman filter combining the GPS and IMU data was developed by integrating position data and heading angles of a triangular array of GPS receivers.The optimized values of two noise covariance matrixes(Q and R)for the Kalman filtering were determined using the Central Composite Design(CCD)method.As compared to the use of a single Garmin GPS receiver,use of the developed GPS/INS system showed improved accuracy performance in terms of both position and heading angle,with reductions in root mean square errors(RMSEs)from 2.7 m to 0.64 m for position and from 8.9ºto 2.1ºfor heading angle.The accuracy improvements show new potential for agricultural auto-guidance applications.展开更多
基金the Korea Evaluation Institute of Industrial Technology(10049017,2014-2016)Agricultural Robotics and Automation Research Center,Korea Institute of Planning and Evaluation for Technology in Food,Agriculture,Forestry and Fisheries(714002-7,2014-2016),Republic of Korea。
文摘The use of low-cost single GPS receivers and inertial sensors for auto-guidance applications has been limited by their reduced accuracy and signal drift over time compared to real-time kinematic(RTK)differential GPS units and fiber-optic gyroscope(FOG)sensors.In this study,a prototype low-cost GPS/INS integrated system consisting of a triangle-shaped array of three Garmin 19x GPS receivers and an Xsens inertial measurement unit(IMU)to improve the accuracy of position and heading angle measured with a single GPS receiver was developed.A triangular algorithm that uses data collected from the three single GPSs mounted on the angular points of a triangular frame was designed.A sensor fusion algorithm based on the Kalman filter combining the GPS and IMU data was developed by integrating position data and heading angles of a triangular array of GPS receivers.The optimized values of two noise covariance matrixes(Q and R)for the Kalman filtering were determined using the Central Composite Design(CCD)method.As compared to the use of a single Garmin GPS receiver,use of the developed GPS/INS system showed improved accuracy performance in terms of both position and heading angle,with reductions in root mean square errors(RMSEs)from 2.7 m to 0.64 m for position and from 8.9ºto 2.1ºfor heading angle.The accuracy improvements show new potential for agricultural auto-guidance applications.
