An Adaptive Weighted Wi-Fi FTM-Based Positioning Method in an NLOS Environment

In the field of indoor positioning, Wi-Fi FTM is a new technology for realizing high-precision positioning. However, errors caused by clock drift and non-line-of-sight (NLOS) signals affect its positioning accuracy. When receiving NLOS signals, most existing algorithms only delete these which decreases number nodes may decrease To address this issue, paper proposed an adapted weighted method under environment. First, includes compensation model to error multipath. Additionally, it can evaluate ranging results improving accuracy assigning greater weight better results. verify effectiveness feasibility method, experiment performed The show that our suitable in completely environment effectively improves Compared with traditional least squares-based inverse distance weighting-based mean outperformed approximately 30% 20% respectively.