The sensing and positioning capabilities foreseen in 6G have great potential for technology advancements in various domains, such as future smart cities and industrial use cases. Channel charting has emerged as a promising technology in recent years for radio frequency-based sensing and localization. However, the accuracy of these techniques is yet far behind the numbers envisioned in 6G. To reduce this gap, in this paper, we propose a novel channel charting technique capitalizing on the time of arrival measurements from surrounding Transmission Reception Points (TRPs) along with their locations and leveraging sensor fusion in channel charting by incorporating laser scanner data during the training phase of our algorithm. The proposed algorithm remains self-supervised during training and test phases, requiring no geometrical models or user position ground truth. Simulation results validate the achievement of a sub-meter level localization accuracy using our algorithm 90% of the time, outperforming the state-of-the-art channel charting techniques and the traditional triangulation-based approaches.

翻译：6G所预见的感知与定位能力在智慧城市和工业应用等众多领域具有巨大的技术发展潜力。近年来，信道制图已成为基于射频感知与定位的一项有前景的技术。然而，这些技术的精度仍远低于6G的预期指标。为缩小这一差距，本文提出一种新颖的信道制图技术，该技术利用周围传输接收点（TRPs）的到达时间测量值及其位置信息，并在算法训练阶段通过融合激光扫描仪数据实现信道制图中的传感器融合。所提算法在训练和测试阶段均保持自监督特性，无需几何模型或用户位置真值。仿真结果验证了该算法在90%的时间内可实现亚米级定位精度，优于现有最先进的信道制图技术及传统三角测量方法。