The global navigation satellite system (GNSS) is the basis for localized crop management by allowing the georeferencing of collected data and the generation of maps by different systems that compose precision agriculture. There is a demand for low-cost navigation systems to enable their use in agriculture. Therefore, the objective of this study is to integrate a low-cost GNSS module to a single-board computer using Kalman filtering to obtain navigation data. The system was evaluated by performing one static and two kinematic experiments, with three repetitions each. In the static experiment, the mean error was 3.25 m with a root mean square error (RMSE) of 3.73 m. In the first kinematic experiment, data variability was lower at a velocity of 1.39 m s(-1). In the second kinematic experiment, the mean error was 1.26 and 1.13 m, and the RMSE was 1.45 and 1.27 m for data obtained before and after filtering, respectively. In conclusion, the system reduces the lateral errors in linear sections but is not indicated for sections that change direction. Moreover, this system can be used in agricultural applications such as soil sampling and crop yield monitoring.
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机译:全球导航卫星系统(GNSS)是本地化作物管理的基础,它允许对收集的数据进行地理配准,并由组成精准农业的不同系统生成地图。人们需要低成本的导航系统,以便使其能够在农业中使用。因此,本研究的目的是使用卡尔曼滤波将低成本的GNSS模块集成到单板计算机上,以获取导航数据。通过进行一次静态实验和两次运动学实验来评估系统,每个实验重复三次。在静态实验中,平均误差为3.25 m,均方根误差(RMSE)为3.73 m。在第一个运动学实验中,数据变异性在1.39 m s(-1)的速度下较低。在第二次运动学实验中,滤波前后获得的数据的平均误差分别为1.26和1.13 m,RMSE分别为1.45和1.27 m。总之,该系统减少了线性截面的横向误差,但不适用于改变方向的截面。此外,该系统还可用于农业应用,例如土壤采样和作物产量监测。
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