An unsupervised machine learning framework using deep embedded clustering (DEC) is proposed to mitigate errors in TDoA UWB indoor localization by selecting high-quality anchor nodes.
An adaptive anchor pairs selection method for ultra-wideband (UWB) Time Difference of Arrival (TDOA) based positioning systems that improves localization accuracy by selecting the optimal anchor pairs for different zones within the coverage area.