A Hybrid GNSS/RSSI Localization Framework for Precision Tractor Navigation: System Evaluation and Analysis
Journal of Smart and Sustainable Farming
Received On : 25 September 2025
Revised On : 10 November 2025
Accepted On : 30 November 2025
Published On : 08 December 2025
Volume 01, 2025
Pages : 224-234
Abstract
Off-road tractor automation needs navigation technology. In that regard, this study discusses a hybrid location-navigation model, which integrates RSSI and GNSS measurements. Two GNSS-enabled DGNSS RTK modules were mounted to a User Portable Device (UPD) alongside a configuration of fixed position wireless routers to measure the RSSI to/from the UPD. The system was tested through various static, dynamic, and real-world scenarios to benchmark the localization capability of the system using a range of available data. The results indicated the DGNSS receiver improved localization to an order of a meter and a min-max based algorithm was shown to be superior to the traditional trilateration method. Various hypothesis to determine signal loss of the model RSSI further improved RSSI based localization and demonstrated system flexibility.
Keywords
Hybrid Localization System, GNSS, RTK-DGNSS, Received Signal Strength Indication (RSSI), Autonomous Navigation, Off-Road Tractor, Positioning Accuracy.
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CRediT Author Statement
The authors confirm contribution to the paper as follows:
Conceptualization: Anandakumar Haldorai and Evelyn Sharma; Methodology: Anandakumar Haldorai; Software: Anandakumar Haldorai; Data Curation: Evelyn Sharma; Writing- Original Draft Preparation: Anandakumar Haldorai; Visualization: Evelyn Sharma; Investigation: Anandakumar Haldorai; Supervision: Anandakumar Haldorai; Validation: Anandakumar Haldorai and Evelyn Sharma; Writing- Reviewing and Editing: Anandakumar Haldorai and Evelyn Sharma; All authors reviewed the results and approved the final version of the manuscript.
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Cite this Article
Anandakumar Haldorai and Evelyn Sharma, “A Hybrid GNSS/RSSI Localization Framework for Precision Tractor Navigation: System Evaluation and Analysis”, Journal of Smart and Sustainable Farming, pp. 224-234, 2025, doi: 10.64026/JSSF/2025022.