Title :
Kalman filtering design for agricultural vehicle state estimation
Author :
Bao Ruixin ; Li Yongkui
Author_Institution :
Eng. Coll., Shenyang Agric. Univ., Shenyang, China
Abstract :
Agricultural vehicle navigation is the key technology of precision agriculture. But some important state parameters can not be tested or the cost is too expensive for implementation. Agricultural vehicle´s dynamics model was established to see which parameter should be measured. The vehicle´ state can be estimated using extended Kalman filtering theory with equation of vehicle´s state, it is helpful for controlling the state of working vehicle.
Keywords :
Kalman filters; agricultural machinery; state estimation; vehicle dynamics; agricultural vehicle dynamics model; agricultural vehicle navigation; agricultural vehicle state estimation; extended Kalman filtering theory; precision agriculture; Aerospace control; Filtering theory; Information filters; Kalman filters; Vehicles; agricultural vehicle navigation; data fusion; extended Kalman filtering theory;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5777685