A ToA-Based Location Algorithm Reducing the NLoS Error under Location-Aware Networks

Precise positioning of agent is a challenging task due to the non line-of-sight (NLoS) propagation in ad-hoc location-aware networks. In an effort to enhance location accuracy, we address a novel scheme to alleviate NLoS error based on the appealing feature of linear lines-of-position (LLoP) and taylor series-least square (TS-LS). This approach utilizes single measurements at a set of anchors and comprises three stages: combination-refine stage, line-of-sight (LoS) reconstruction and taylor-optimization. The second stage reconstructs the true ranges by subtracting the NLoS measurements from the maximum measurement residual. Simulation results and discussions are given to evaluate the performance in typical NLoS environments. The conclusions infer that the proposed algorithm outperforms the traditional algorithms in dense NLoS environment at a reasonable computational complexity.