UWB

Ultra-wideband (UWB) has attracted much attention in indoor positioning due to its high accuracy, low power consumption, and excellent anti-jamming capability. However, due to the complexity of the usage environment, UWB signals are often obstructed by objects such as metals and walls, leading to non-line-of-sight (NLOS) conditions and a decrease in positioning accuracy. To fully consider the effect of ranging errors caused by different occlusions on UWB signals, firstly, this paper analyzes the attenuation characteristics of UWB in different NLOS scenarios. By combining the channel impulse correspondence (CIR) and Markov Transition Field (MTF), an efficient classification method for NLOS identification is proposed. Further, for the signal attenuation characteristics in different scenarios, this paper proposes a polynomial fitting based on the Negative Log-Likelihood function (NLLPF), which greatly mitigates the ranging errors caused by different occlusions. Additionally, the dynamic scene adaptation of UWB localization is enhanced by fusing the Inertial Measurement Unit (IMU) using a confidence-considering EKF (CEKF). Finally, experimental results show that in indoor scenarios, the proposed method achieves a mean absolute error (MAE) of 5.60 cm, while in corridor scenarios, the MAE is 16.36 cm, significantly lower than the 12.42 cm and 54.88 cm of the original methods. 

超宽带（Ultra-wideband, UWB）凭借高精度、低功耗与优异的抗干扰能力，在室内定位领域受到广泛关注。然而由于应用环境复杂，UWB信号常受到金属、墙体等物体遮挡，引发非视距（NLOS）场景，进而导致定位精度下降。为充分考量不同遮挡对UWB信号产生的测距误差影响，本文首先分析了UWB在各类非视距场景下的衰减特性。通过结合信道冲激响应（Channel Impulse Response, CIR）与马尔可夫转移场（Markov Transition Field, MTF），本文提出了一种高效的非视距识别分类方法。进一步，针对不同场景下的信号衰减特性，本文提出了基于负对数似然函数的多项式拟合（Negative Log-Likelihood function based Polynomial Fitting, NLLPF）方法，可有效缓解各类遮挡引发的测距误差。此外，通过采用考虑置信度的扩展卡尔曼滤波（Confidence-considering Extended Kalman Filter, CEKF）融合惯性测量单元（Inertial Measurement Unit, IMU）数据，提升了UWB定位在动态场景下的适配能力。最后，实验结果表明，在室内场景中，本文所提方法的平均绝对误差（Mean Absolute Error, MAE）为5.60厘米；而在走廊场景中，其MAE为16.36厘米，显著低于原有方法的12.42厘米与54.88厘米。

搜集汇总

背景与挑战

背景概述

该数据集聚焦于UWB（超宽带）技术的高精度定位系统，包含信号预处理和定位架构数据，用于分析非视距环境下的信号衰减特性，并通过数据融合方法校正测量误差。数据集文件包括Excel和文本格式，主要用于UWB定位坐标解算，适用于复杂环境中的定位研究。