Error Mitigation for TDoA UWB Indoor Localization using Unsupervised Machine Learning

arXiv:2404.06824v1 Announce Type: new
Abstract: Indoor positioning systems based on Ultra-wideband (UWB) technology are gaining recognition for their ability to provide cm-level localization accuracy. However, these systems often encounter challenges caused by dense multi-path fading, leading to positioning errors. To address this issue, in this letter, we propose a novel methodology for unsupervised anchor node selection using deep embedded clustering (DEC). Our approach uses an Auto Encoder (AE) before clustering, thereby better separating UWB features into separable clusters of UWB …

abstract accuracy arxiv challenges cs.lg error errors however issue localization machine machine learning path recognition systems technology type unsupervised unsupervised machine learning