NLOS occlusion UWB TOA ranging dataset in indoor environment
we propose a novel Non-Line-of-Sight (NLOS) identification and error-mitigation method for dynamic object positioning and ultra-wideband (UWB) ranging. By applying inverse estimation on known Anchor Points (Aps) and improved unscented Kalman filter (IRUKF), the proposed technology identifies and compensates for NLOS occlusions between tag and APs, reducing positioning errors. The approach has been verified through simulation and experiment, with identification precision of 97.02%. After mitigating errors, we observed significant error reductions of 91.80%, 98.90% in Line-of-sight (LOS), NLOS situations, respectively. Moreover, the developed IRUKF algorithm effectively minimizes mislocalization by 50.48% in harsh scenarios. This data is collected by IMCM laboratory, including "Z", "U", "O" three dynamic tracking positioning trajectories
The data set can be read by the Matlab import tool or through the supplied import function. More complete data are available in the paper "A Novel NLOS Identification and Error Mitigation Method for UWB Ranging and Positioning" in IEEE COMMUNICATIONS LETTERS uploaded after publication.