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Evaluating the navigation performance of multi-information integration based on low-end inertial sensors for precision agriculture
Precision Agriculture ( IF 6.2 ) Pub Date : 2020-08-14 , DOI: 10.1007/s11119-020-09747-x
Quan Zhang , Qijin Chen , Zhengpeng Xu , Tisheng Zhang , Xiaoji Niu

The main objective of this research was to evaluate the navigation performance of multi-information integration based on a low-end inertial measurement unit (IMU) in precision agriculture by utilizing different auxiliary information (i.e., GNSS real-time kinematic (RTK), non-holonomic constraints (NHC) and dual antenna GNSS). A series of experiments with different operation scenes (e.g., open sky in wet and dry soils) were carried out for quantitative analysis. For the position drift error during a 20-s GNSS outage, the dual-antenna GNSS-assisted approach did not provide a reduction, and the NHC reduced the maximum error in the lateral and vertical directions by over 80% in the dry soil test, but only by approximately 30% in the wet soil test. The heading error with continuous GNSS assistance can be less than 0.03° and be reduced by more than 90% with the aid of dual-antenna GNSS. Additionally, the NHC reduced the heading error from 0.54° to 0.21° and from 0.34° to 0.25° in the dry and wet soil tests respectively. The results suggested that the multi-information integration improved the positioning and orientation reliability. Moreover, the lateral positioning accuracy required for the control of agriculture autonomous vehicles was achieved at approximately 3.0 mm with over a 60% accuracy improvement brought by the dual-antenna GNSS assistance. In contrast to the vulnerability of a single system, multi-information integration can provide comprehensive navigation information with higher reliability and lower costs. Hence, multi-information fusion will be a great opportunity for agriculture to meet the high-accuracy and high-reliability requirements of precision agriculture.

中文翻译:

基于低端惯性传感器的精准农业多信息融合导航性能评估

本研究的主要目的是评估基于低端惯性测量单元(IMU)的多信息集成在精准农业中的导航性能,利用不同的辅助信息(即 GNSS 实时运动学(RTK),非-完整约束 (NHC) 和双天线 GNSS)。进行了一系列不同操作场景(例如,潮湿和干燥土壤中的开阔天空)的实验以进行定量分析。对于 20 秒 GNSS 中断期间的位置漂移误差,双天线 GNSS 辅助方法没有提供减少,NHC 在干土测试中将横向和垂直方向的最大误差减少了 80% 以上,但在湿土测试中仅下降约 30%。连续 GNSS 辅助下的航向误差可以小于 0。03°,并在双天线 GNSS 的帮助下减少 90% 以上。此外,NHC 在干和湿土壤测试中分别将航向误差从 0.54° 减少到 0.21° 和从 0.34° 减少到 0.25°。结果表明,多信息集成提高了定位和定向的可靠性。此外,农业自动驾驶车辆控制所需的横向定位精度达到了约 3.0 mm,双天线 GNSS 辅助带来的精度提升超过 60%。相对于单一系统的脆弱性,多信息集成可以提供可靠性更高、成本更低的综合导航信息。因此,
更新日期:2020-08-14
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