3 papers
cs.LG2024
Bluetooth Low Energy Dataset Using In-Phase and Quadrature Samples for Indoor Localization
Samuel G. Leitch, Qasim Zeeshan Ahmed, Ben Van Herbruggen +5
One significant challenge in research is to collect a large amount of data and learn the underlying relationship between the input and the output variables. This paper outlines the…
eess.SP2024
Removing the need for ground truth UWB data collection: self-supervised ranging error correction using deep reinforcement learning
Dieter Coppens, Ben Van Herbruggen, Adnan Shahid +1
Indoor positioning using UWB technology has gained interest due to its centimeter-level accuracy potential. However, multipath effects and non-line-of-sight conditions cause rangin…
cs.LG2024
Error Mitigation for TDoA UWB Indoor Localization using Unsupervised Machine Learning
Phuong Bich Duong, Ben Van Herbruggen, Arne Broering +2
Indoor positioning systems based on Ultra-wideband (UWB) technology are gaining recognition for their ability to provide cm-level localization accuracy. However, these systems ofte…