基于超宽带的实时定位的完整解决方案
Vlad Ratiu1,2, Ovidiu Ratiu2, Olivier Raphael Smeyers3
1Computer Science Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
本研究介绍了使用超宽带 (UWB) 技术和混合机器学习的实时定位系统. 它显著减少了对准确,高频位置跟踪的计算需求.
科学领域:
- 工程 工程师 工程师 工程师
- 计算机科学 计算机科学
- 信号处理 信号处理
背景情况:
- 实时定位系统 (RTPS) 对于各种应用,从工业到商业用途至关重要.
- 无线电频率 (RF) 系统通常使用飞行时间 (ToF) 和抵达时间差 (TDoA) 来定位.
- 由于对多层算法的高计算需求,TDoA系统经常面临局限性.
研究的目的:
- 使用超宽带 (UWB) 技术设计,实施和验证基于TDoA的新型RTPS.
- 克服高频定位现有TDoA系统中的计算限制.
- 为了提高定位精度,同时降低计算功率要求.
主要方法:
- 使用UWB技术开发基于TDoA的完整的硬件和软件RTPS.
- 混合机器学习 (ML) 解决方案的集成与算法微调.
- 对系统性能与最先进的解决方案进行验证和验证.
主要成果:
- 证明了对TDoA定位所需的计算功率的显著减少.
- 实现了高频标签位置更新率与所需的准确性.
- 成功地解决了传统TDoA多层算法的局限性.
结论:
- 开发的UWB TDoA系统为实时定位提供了高效准确的解决方案.
- 混合ML和算法调整有效地减轻了TDoA系统中的计算挑战.
- 这种方法推进了实时定位系统 (RTLS) 的最新技术.
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