UWB DW1000 Dataset for indoor environments

The accurate distinction between line-of-sight (LOS) and non-line-of-sight (NLOS) propagation channels is paramount for precise distance measurement within ultra-wideband (UWB) indoor localization systems. In complex and dynamic environments, such as those encountered in the indoor positioning of autonomous mobile robots or vehicles, UWB signal propagation is particularly susceptible to NLOS conditions. However, much of the existing literature focuses on binary LOS/NLOS classifications, often overlooking the complexities of real-world environments such as hard-NLOS and multipath conditions. Additionally, a dynamic adaptation model for diverse indoor environments is lacking. This omission impedes the accuracy of UWB localization applications, such as autonomous robotics, where precision is vital in complex indoor settings. The real measurement data were conducted in two residential environments encompassing multiple rooms that were selected for the measurement campaign to cover the variable influence of indoor environments on RF signal propagation. The data required for our experimental evaluations were gathered in four rooms of varying dimensions (5 m × 4 m, 10 m x 4 m, 20 m x 6 m, and 4 m x 2 m) within a building environment, a hall measuring 8 m × 48 m containing various items of furniture, and two corridors with widths of 3 m and 1.5 m, respectively. These measurement data were collected under different propagation channels across these diverse scenarios. For the NLOS experiments within our project, the setup required the creation of obstacles between the anchor and target transceivers to simulate NLOS conditions, necessitating the use of two different rooms. In particular, this work has focused on the analysis of soft and hard NLOS propagation channels, which helps in understanding how different obstacles may affect UWB signal transmission. The illustration scenario in which the signal emitted from a tag device is received by anchor nodes under several conditions in a situation where an UWB transceiver, Qorvo DW 1000, acts as both the tag device and the anchor nodes. 

视距（Line-of-Sight, LOS）与非视距（Non-Line-of-Sight, NLOS）传播信道的精准区分，对于超宽带（Ultra-wideband, UWB）室内定位系统中的高精度距离测量至关重要。在复杂动态环境中，如自主移动机器人或车辆的室内定位场景，UWB信号传播极易受到NLOS信道影响。然而，现有大量研究多聚焦于二分类LOS/NLOS识别任务，往往忽略了现实环境中硬非视距（hard-NLOS）与多径效应等复杂场景。此外，当前仍缺乏适配多样化室内环境的动态自适应模型，这一缺陷限制了自主机器人等对定位精度要求极高的复杂室内UWB定位应用的性能表现。

本次实测数据采集自两处包含多间房间的住宅环境，该采集场景旨在覆盖室内环境对射频（Radio Frequency, RF）信号传播的可变影响。本实验评估所需的数据采集于一栋建筑内的4间不同尺寸房间（5 m × 4 m、10 m × 4 m、20 m × 6 m及4 m × 2 m）、一间摆放各类家具的8 m × 48 m大厅，以及两条宽度分别为3 m和1.5 m的走廊。上述数据在多样化场景下的不同传播信道条件中采集得到。

本项目的NLOS实验需在锚节点与目标收发器之间设置障碍物以模拟NLOS信道，因此需要借助两间不同的房间完成实验部署。本研究重点分析了软、硬NLOS传播信道，以明晰不同障碍物对UWB信号传输的影响机制。本实验的场景示意图如下：以Qorvo DW1000作为标签设备与锚节点，实现标签发射的信号在多种条件下被锚节点接收的场景。

搜集汇总

背景与挑战

背景概述

该数据集提供了在多种室内环境中收集的UWB信号传播数据，特别关注了LOS/NLOS条件，包括硬NLOS和多路径效应，旨在提高复杂室内环境下UWB定位的精度。数据采集于不同尺寸的房间、走廊和大厅，模拟了多种障碍物条件下的信号传播情况。