TOA-based NLOS error mitigation algorithm for 3D indoor localization
Weigang Wang, Yunwei Zhang, Longbin Tian
Abstract
In the process of indoor localization, the existence of the non-line of sight (NLOS) error will greatly reduce the localization accuracy. To reduce the impact of this error, a 3 dimensional (3D) indoor localization algorithm named LMR (LLS-Minimum-Re-sidual) is proposed in this paper. We first estimate the NLOS error and use it to correct the measurement distances, and then calculate the target location with linear least squares (LLS) solution. The final nodes location can be obtained accurately by NLOS error mitigation. Our algorithm can work efficiently in both indoor 2D and 3D environments. The simulation results show that the proposed algorithm has better performance than traditional algorithms and it can significantly improve the localization accuracy.