Multi-Scenario Variable-State Robust Fusion Algorithm for Ranging Analysis Framework

Kaiting Xie, Zhaoguo Zhang () and Faan Wang
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Kaiting Xie: The Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China
Zhaoguo Zhang: The Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China
Faan Wang: The Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China

Agriculture, 2024, vol. 14, issue 4, 1-20

Abstract: Integrating modern information technology with traditional agriculture has made agricultural machinery navigation essential in PA (precision agriculture). However, agricultural equipment faces challenges such as low positioning accuracy and poor algorithm adaptability due to the complex farmland environment and various operational requirements. In this research, we proposed a generalized ranging theoretical framework with multi-scenario variable-state fusion to improve the GNSS (Global Navigation Satellite System) observation exchange performance among agricultural vehicles, and accurately measure IVRs (inter-vehicular ranges). We evaluated the effectiveness of three types of GNSS observations, including PPP-SD (precise single point positioning using single difference), PPP-TCAR (precise single point positioning using double difference based on three-carrier ambiguity resolution), and PPP-LAMBDA (precise single point positioning using double difference based on least-squares ambiguity decorrelation adjustment). Moreover, we compared the accuracy of IVRs measurements. Our framework was validated through field experiments in different scenarios. It provides insights into the appropriate use of different positioning algorithms based on the application scenario, application objects, and motion states.

Keywords: precision agriculture; GNSS; theoretical framework; precise single point positioning; inter-vehicular ranges (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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