Fusion technology in integrated positioning system for autonomous agricultural vehicles

One integrated positioning system, consisting of a GPS receiver and inertial sensors, can be used to improve positioning accuracy for autonomous agricultural vehicles. The fusion technology has been proven to be effective in improving the accuracy in such vehicle integrated positioning system. This paper presents three applications of fusion technologies that have been investigated for land autonomous navigation vehicle: federated method based Kalman filter for the Inertial Navigation System (INS) Global Position System (GPS)/Communicational Navigation System (CNS) integrated navigation system; Kalman filter that designed to integrate the readings from GPS and Inertial Measurement Unit (IMU) for providing an accurate dynamic positioning signal. A Position-Velocity-Attitude (PVA) model-based fusion algorithm developed for Garmin GPS with solid state inertial sensors integrated system.