Next Article in Journal
Next Article in Special Issue
Previous Article in Journal
Previous Article in Special Issue
Sensors 2013, 13(11), 15307-15323; doi:10.3390/s131115307
Article

A Kalman Filter Implementation for Precision Improvement in Low-Cost GPS Positioning of Tractors

1,* , 1
, 1
 and 2
Received: 3 September 2013; in revised form: 3 November 2013 / Accepted: 4 November 2013 / Published: 8 November 2013
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2013)
View Full-Text   |   Download PDF [500 KB, updated 21 June 2014; original version uploaded 21 June 2014]
Abstract: 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.
Keywords: Kalman filter; agricultural vehicle; Global Positioning System (GPS); vehicle guidance; sensor data fusion; autonomous navigation Kalman filter; agricultural vehicle; Global Positioning System (GPS); vehicle guidance; sensor data fusion; autonomous navigation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Gomez-Gil, J.; Ruiz-Gonzalez, R.; Alonso-Garcia, S.; Gomez-Gil, F.J. A Kalman Filter Implementation for Precision Improvement in Low-Cost GPS Positioning of Tractors. Sensors 2013, 13, 15307-15323.

AMA Style

Gomez-Gil J, Ruiz-Gonzalez R, Alonso-Garcia S, Gomez-Gil FJ. A Kalman Filter Implementation for Precision Improvement in Low-Cost GPS Positioning of Tractors. Sensors. 2013; 13(11):15307-15323.

Chicago/Turabian Style

Gomez-Gil, Jaime; Ruiz-Gonzalez, Ruben; Alonso-Garcia, Sergio; Gomez-Gil, Francisco J. 2013. "A Kalman Filter Implementation for Precision Improvement in Low-Cost GPS Positioning of Tractors." Sensors 13, no. 11: 15307-15323.



Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert