Hard/Soft NLoS Detection via Combinatorial Data Augmentation for 6G Positioning
This paper proposes the combinatorial data augmentation-guided NLoS detection (CDA-ND) algorithm, which generates NLoS evidence vectors from multilateration-based location clusters to enable both hard and soft NLoS detection modes, significantly improving 6G positioning accuracy in indoor factory environments by reducing mean absolute error by up to 66%.
Sang-Hyeok Kim (Inha University, South Korea), Seung Min Yu (Korea Railroad Research Institute, South Korea), Jihong Park (Singapore University of Technology and Design, Singapore), Seung-Woo Ko (Inha University, South Korea)2026-03-10🔢 math