RT info:eu-repo/semantics/article
T1 A kalman filter implementation for precision improvement in low-cost GPS positioning of tractors
A1 Gómez Gil, Jaime
A1 Ruiz González, Rubén
A1 Alonso García, Sergio
A1 Gómez Gil, Francisco Javier
K1 Kalman filter
K1 Agricultural vehicles
K1 Global Positioning System (GPS)
K1 Vehicle guidance
K1 Sensor data fusion
K1 33 Ciencias Tecnológicas
AB Low-cost GPS receivers provide geodetic positioning information using the NMEA protocol, usually with eight digits for latitude and nine digits for longitude. When these geodetic coordinates are converted into Cartesian coordinates, the positions fit in a quantization grid of some decimeters in size, the dimensions of which vary depending on the point of the terrestrial surface. The aim of this study is to reduce the quantization errors of some low-cost GPS receivers by using a Kalman filter. Kinematic tractor model equations were employed to particularize the filter, which was tuned by applying Monte Carlo techniques to eighteen straight trajectories, to select the covariance matrices that produced the lowest Root Mean Square Error in these trajectories. Filter performance was tested by using straight tractor paths, which were either simulated or real trajectories acquired by a GPS receiver. The results show that the filter can reduce the quantization error in distance by around 43%. Moreover, it reduces the standard deviation of the heading by 75%. Data suggest that the proposed filter can satisfactorily preprocess the low-cost GPS receiver data when used in an assistance guidance GPS system for tractors. It could also be useful to smooth tractor GPS trajectories that are sharpened when the tractor moves over rough terrain.
PB MDPI
SN 1424-8220
YR 2013
FD 2013
LK https://uvadoc.uva.es/handle/10324/57820
UL https://uvadoc.uva.es/handle/10324/57820
LA eng
NO Sensors, 2013, vol. 13, n. 11, p. 15307-15323
NO Producción Científica
DS UVaDOC
RD 12-sep-2024