基于ANN的LiDAR定位系统用于B5G
Egidio Raimundo Neto1, Matheus Ferreira Silva1, Tomás P V Andrade1
1Laboratory WOCA, National Institute of Telecommunications (Inatel), 510 João de Camargo Av., Santa Rita do Sapucaí 37540-000, MG, Brazil.
Micromachines
|May 25, 2024
概括
本研究介绍了一种先进的室内定位系统,使用二维光探测和测距 (LiDAR) 和人工神经网络 (ANN). 该系统实现了超越5G移动网络的高精度,改善了行人位置映射.
科学领域:
- 机器人和自动化 机器人和自动化
- 无线通信系统无线通信系统
- 人工智能的人工智能
背景情况:
- 超越第五代 (B5G) 移动网络需要复杂的室内传感和定位.
- 传统的基于射频的方法在准确性和电磁干扰方面存在局限性.
- 精确的室内定位对于优化天线阵列控制等网络功能至关重要.
研究的目的:
- 为B5G网络开发一个高效和精确的室内定位系统.
- 利用由人工神经网络 (ANN) 增强的二维光检测和测距 (LiDAR) 技术.
- 在复杂的室内环境中克服感知和定位的挑战.
主要方法:
- 实现一个与人工神经网络 (ANN) 集成的2D-LiDAR系统.
- 使用2D-LiDAR传感器进行数据采集和数字过器进行信号增强.
- 采用摄像头和图像处理用于自动化的ANN培训样本标签.
主要成果:
- 该系统在绘制行人位置时表现出高性能.
- 实现了高达98.787%的精度,95.25%的准确性,98.537%的回忆,以及98.571%的F1得分.
- 对抗电磁干扰的ANN强度证实了比RF方法更高的性能.
结论:
- 拟议的2D-LiDAR和ANN系统为室内定位提供了可靠和准确的解决方案.
- 它有效地解决了B5G移动网络的苛刻要求.
- 该系统显示了增强室内传感和定位应用的巨大潜力.
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