基于双模型的无人机改进的UWB室内定位方法
Zhengrong Xiang1,2, Lei Chen1, Qiqi Wu1
1School of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
这项研究引入了无人机的双超宽带 (UWB) 定位系统,降低了部署成本. 这种新的方法实现了十米级的精度,超过了传统的三系统.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 导航系统 导航系统
- 传感器融合式传感器
背景情况:
- 超宽带 (UWB) 技术为无人机 (UAV) 室内定位提供了卓越的范围性能.
- 传统的UWB定位需要至少三个点进行3D本地化,从而增加了部署的复杂性和成本.
- 减少的数量对于实用和经济的无人机导航系统至关重要.
研究的目的:
- 开发一个具有成本效益的无人机定位模型,只使用两个UWB.
- 通过整合来自多个传感器的数据来提高定位准确性,包括测距仪,气压计和加速度计.
- 通过融合测距仪和气压计数据来提高高度测量的可靠性.
主要方法:
- 提出了一种双定位模型,将3D定位投射到2D水平平面上,使用测距仪的高度数据.
- 开发了一种高度融合方法,以整合测距仪和气压计数据,使气压计校准和避开障碍物成为可能.
- 无气味卡尔曼波器 (UKF) 算法用于多传感器数据融合,将UWB,测距仪,气压计和加速度计数据结合起来.
主要成果:
- 双模型成功地将3D定位转换为2D定位,精确度提高.
- 高度融合方法提高了高度测量可靠性,减轻了地面障碍所造成的问题.
- 模拟和实验表明,双模型实现了十米级的定位精度,超过了三模型.
结论:
- 拟议的双定位模型为无人机室内导航提供了可行和准确的解决方案.
- 使用UKF的多传感器数据融合显著提高了双系统中的定位精度.
- 这种方法为无人机的传统多UWB定位系统提供了一种实用且具有成本效益的替代方案.
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