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Performance Analysis of Relative GPS Positioning for Low-Cost Receiver-Equipped Agricultural Rovers.

Gustavo S Carvalho¹, Felipe O Silva¹, Marcus Vinicius O Pacheco¹

¹Department of Automatics, Federal University of Lavras, Lavras 37203-202, Brazil.

Sensors (Basel, Switzerland)

|November 14, 2023

Summary

This summary is machine-generated.

Relative Global Navigation Satellite Systems (RGNSS) can achieve 1.5 m accuracy for agricultural applications, even with communication failures and long distances. This technology is crucial for precision agriculture and autonomous vehicle guidance.

Keywords:

RGNSS baseline separation communication failure moving rover positioning accuracy precision agriculture

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Area of Science:

Geomatics Engineering
Agricultural Technology
Satellite Navigation Systems

Background:

Global Navigation Satellite Systems (GNSS) are essential for positioning, navigation, and timing across various sectors.
Standard GPS accuracy (up to 10 m) is insufficient for modern precision agriculture (PA) and autonomous vehicle applications requiring sub-meter precision.
Relative GNSS (RGNSS) techniques can mitigate common-mode errors to improve positioning accuracy.

Purpose of the Study:

To investigate the sensitivity of low-cost RGNSS positioning accuracy in agricultural rovers.
To analyze the impact of communication failures and baseline distances on RGNSS performance.
To determine the feasibility of achieving SAE J2945 standard accuracy (1.5 m horizontal at 1σ) in agricultural contexts.

Main Methods:

Utilized an extended Kalman filter (EKF) for position estimation.
Evaluated RGNSS performance under varying communication failure durations and baseline separations.
Employed experimental data from the Brazilian Network for Continuous Monitoring of GNSS (RBMC) and a real-world agricultural rover.

Main Results:

Achieved 1.5 m horizontal accuracy at 68% probability (1σ).
Maintained this accuracy with communication failures up to 3000 seconds.
Sustained accuracy with baseline separations of approximately 1500 km.

Conclusions:

Low-cost RGNSS, combined with EKF, can meet stringent accuracy requirements for precision agriculture.
The RGNSS technique is robust against significant communication outages and large inter-receiver distances.
This research validates the practical application of RGNSS for autonomous guidance in Agriculture 4.0.