ORIGINAL ARTICLE
A comparative analysis of the performance of various GNSS positioning concepts dedicated to precision agriculture
1
Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, C.K. Norwida 25, 50-375 Wrocław, Poland
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article
Submission date: 2023-12-04
Final revision date: 2023-12-20
Acceptance date: 2023-12-28
Publication date: 2023-02-02
Corresponding author
Tomasz Hadas
Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Norwida 25, 50-375, Wrocław, Poland
Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Norwida 25, 50-375, Wrocław, Poland
Reports on Geodesy and Geoinformatics 2024;117:11-20
KEYWORDS
TOPICS
ABSTRACT
Automated guidance systems for precision agriculture rely on Global Navigation Satellite Systems (GNSS) and correction services for high accuracy and precision in field operations. This study evaluates the performance of selected GNSS positioning services for precision agriculture in a field experiment. We use three correction services: SF1, SF3, and RTK, which apply varying positioning concepts, i.e., Wide Area Differential GNSS, Precise Point Positioning, and Real-Time Kinematics, respectively. The tractor is autonomously steered along multiple predefined paths located in open-sky areas as well as near the heavy tree cover. The reference route of the vehicle is determined by classical surveying. Tractor trajectories, a SF1 and SF3 corrections, are shifted from predefined straight paths, unlike in the case for RTK. Offsets of up to several decimeters are service- and area-specific, indicating an issue with the stability of the reference frame. Additionally, the varying performance of the correction services implies that environmental conditions limit the precision and accuracy of GNSS positioning in precision agriculture. The pass-to-pass analysis reveals that SF1 improves the declared accuracy, while SF3 is less reliable in obstructed areas. RTK remains a stable source for determining position. Under favorable conditions, the pass-to-pass accuracy at 95\% confidence level is better than 11.5 cm, 8.5 cm, and 4.5 cm for SF1, SF3, and RTK, respectively. In the worst-case scenario, the corresponding accuracies are: 25.5 cm, 65.5 cm, and 22.5 cm.
ACKNOWLEDGEMENTS
The authors acknowledge "Agripuls Wiesław Kowalczyk" for providing the tractor equipped with the Starfire 6000 receiver for the time of experiment. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
REFERENCES (33)
1.
Adamchuk, V. I. (2008). Satellite-based auto-guidance. University of Nebraska at Lincoln Extension Circular, EC706, Lincoln, Nebraska, on-line, Last accessed: 2023.12.
2.
Bak, T. and Jakobsen, H. (2004). Agricultural robotic platform with four wheel steering for weed detection. Biosystems Engineering, 87(2):125–136, doi:10.1016/j.biosystemseng.2003.10.009.
3.
Bell, T. (2000). Automatic tractor guidance using carrier-phase differential GPS. Computers and Electronics in Agriculture, 25(1–2):53–66, doi:10.1016/s0168-1699(99)00055-1.
4.
Catania, P., Comparetti, A., Febo, P., Morello, G., Orlando, S., Roma, E., and Vallone, M. (2020). Positioning accuracy comparison of GNSS receivers used for mapping and guidance of agricultural machines. Agronomy, 10(7):924, doi:10.3390/agronomy10070924.
5.
Cheein, F. A. A. and Carelli, R. (2013). Agricultural robotics: Unmanned robotic service units in agricultural tasks. IEEE Industrial Electronics Magazine, 7(3):48–58, doi:10.1109/mie.2013.2252957.
6.
Coyne, P., Casey, S., and Milliken, G. (2003). Comparison of differentially corrected GPS sources for support of site-specific management in agriculture. Kansas State University. Agricultural Experiment Station and Cooperative Extension Service.
7.
Esau, T. J., MacEachern, C. B., Farooque, A. A., and Zaman, Q. U. (2021). Evaluation of autosteer in rough terrain at low ground speed for commercial wild blueberry harvesting. Agronomy, 11(2):384, doi:10.3390/agronomy11020384.
8.
Guo, J., Li, X., Li, Z., Hu, L., Yang, G., Zhao, C., Fairbairn, D., Watson, D., and Ge, M. (2018). Multi-GNSS precise point positioning for precision agriculture. Precision Agriculture, 19(5):895–911, doi:10.1007/s11119-018-9563-8.
9.
Harbuck, T. L., Fulton, J. P., McDonald, T. P., and Brodbeck, C. J. (2006). Evaluation of GPS autoguidance systems over varying time periods. In 2006 ASAE Annual Meeting, Portland, Oregon, July 9-12, 2006, por2006. American Society of Agricultural and Biological Engineers, doi:10.13031/2013.21978.
10.
He, L. (2022). Variable rate technologies for precision agriculture. In Zhang, Q., editor, Encyclopedia of Smart Agriculture Technologies, page 1–9. Springer International Publishing, doi:10.1007/978-3-030-89123-7_34-2.
11.
Huisman, L. and de Ligt, H. (2023). Validation of reference frame consistency of GNSS service products. In International Association of Geodesy Symposia. Springer Berlin Heidelberg, doi:10.1007/1345_2023_232.
12.
Huuskonen, J. and Oksanen, T. (2018). Soil sampling with drones and augmented reality in precision agriculture. Computers and Electronics in Agriculture, 154:25–35, doi:10.1016/j.compag.2018.08.039.
13.
Huyghebaert, B., Dubois, G., Defays, G., Namur, C. D., and Gembloux, B. (2013). Actual and global precision of the guidance system AutoTrac from John Deere. In EFITA-WCCA-CIGR Conference, Sustainable Agriculture through ICT innovation, Turin, Italy, 2013.
14.
International Organization for Standardization (2010). Tractors and machinery for agriculture and forestry – test procedures for positioning and guidance systems in agriculture (ISO Standard No. 12188-1:2010). https://www.iso.org/standard/5....
15.
Karaim, M., Elsheikh, M., and Noureldin, A. (2018). GNSS error sources. In Multifunctional Operation and Application of GPS. InTech, doi:10.5772/intechopen.75493.
16.
Kee, C., Parkinson, B. W., and Axelrad, P. (1991). Wide area differential GPS. Navigation, 38(2):123–145, doi:10.1002/j.2161-4296.1991.tb01720.x.
17.
Keicher, R. and Seufert, H. (2000). Automatic guidance for agricultural vehicles in Europe. Computers and Electronics in Agriculture, 25(1–2):169–194, doi:10.1016/s0168-1699(99)00062-9.
18.
Kim, J. H., Moon, H. C., Woo, H. J., Zhe, H. X., Kim, H. J., Kim, Y. J., and Kye, J. E. (2013). Auto-guidance system for tillage tractor. In 2013 13th International Conference on Control, Automation and Systems (ICCAS 2013). IEEE, doi:10.1109/iccas.2013.6704165.
19.
Lange, A. F. and Peake, J. (2020). Precision agriculture. In Morton, Y., Diggelen, F., Spilker, J., Parkinson, B. W., Lo, S., and Gao, G., editors, Position, Navigation, and Timing Technologies in the 21st Century, page 1735–1747. Wiley, doi:10.1002/9781119458555.ch56.
20.
Luck, J., Pitla, S., Shearer, S., Mueller, T., Dillon, C., Fulton, J., and Higgins, S. (2010). Potential for pesticide and nutrient savings via map-based automatic boom section control of spray nozzles. Computers and Electronics in Agriculture, 70(1):19–26, doi:10.1016/j.compag.2009.08.003.
21.
Mawardi, M., Nugraheni, P., Sutiarso, L., Virgawati, S., and Fuadi, M. (2018). Mapping the Variable-Rate Application (VRA) of precision fertilizing for soybean. Journal of Advanced Research in Applied Mechanics, 51(1):1–9.
22.
Montenbruck, O., Steigenberger, P., and Hauschild, A. (2020). Comparing the ‘Big 4’ – a user’s view on GNSS performance. In 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS). IEEE, doi:10.1109/plans46316.2020.9110208.
23.
Onyango, C. M., Nyaga, J. M., Wetterlind, J., Söderström, M., and Piikki, K. (2021). Precision agriculture for resource use efficiency in smallholder farming systems in Sub-Saharan Africa: A systematic review. Sustainability, 13(3):1158, doi:10.3390/su13031158.
24.
Perez-Ruiz, M., Slaughter, D. C., Gliever, C., and Upadhyaya, S. K. (2012). Tractor-based Real-time Kinematic-Global Positioning System (RTK-GPS) guidance system for geospatial mapping of row crop transplant. Biosystems Engineering, 111(1):64–71, doi:10.1016/j.biosystemseng.2011.10.009.
25.
Pini, M., Marucco, G., Falco, G., Nicola, M., and De Wilde, W. (2020). Experimental testbed and methodology for the assessment of RTK GNSS receivers used in precision agriculture. IEEE Access, 8:14690–14703, doi:10.1109/access.2020.2965741.
26.
Radočaj, D., Plaščak, I., and Jurišić, M. (2023). Global Navigation Satellite Systems as state-of-the-art solutions in precision agriculture: A review of studies indexed in the Web of Science. Agriculture, 13(7):1417, doi:10.3390/agriculture13071417.
27.
Reid, J. F. and Searcy, S. W. (1987). Automatic tractor guidance with computer vision. SAE transactions, 96:673–693.
28.
Schönemann, E. (2014). Analysis of GNSS raw observations in PPP solutions. PhD thesis, Technische Universität Darmstadt.
29.
Stombaugh, T. (2018). Satellite-based Positioning Systems for Precision Agriculture, page 25–35. American Society of Agronomy and Soil Science Society of America, doi:10.2134/precisionagbasics.2017.0036.
30.
Teunissen, P. J. G. and Khodabandeh, A. (2015). Review and principles of PPP-RTK methods. Journal of Geodesy, 89(3):217–240, doi:10.1007/s00190-014-0771-3.
31.
Tran, H. T., Cao, W., Reutemann, M., Dai, L., Ostermeier, R., and Kormann, G. (2020). GNSS positioning and navigation - a foundational element of digital farming. In 2020 European Navigation Conference (ENC). IEEE, doi:10.23919/enc48637.2020.9317529.
32.
Zabalegui, P., De Miguel, G., Perez, A., Mendizabal, J., Goya, J., and Adin, I. (2020). A review of the evolution of the integrity methods applied in GNSS. IEEE Access, 8:45813–45824, doi:10.1109/access.2020.2977455.
33.
Zumberge, J. F., He in, M. B., Jefferson, D. C., Watkins, M. M., and Webb, F. H. (1997). Precise point positioning for the efficient and robust analysis of GPS data from large networks. Journal of Geophysical Research: Solid Earth, 102(B3):5005–5017, doi:10.1029/96jb03860.
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