# A Localization Enhancement Method Based on Direct-Path Identification and Tracking for Future Networks

## TL;DR

This paper introduces a new method to improve localization accuracy in IoT networks by identifying and tracking direct signal paths in challenging environments.

## Contribution

A novel localization enhancement method is proposed, based on direct-path identification and tracking to reduce errors in NLOS scenarios.

## Key findings

- The proposed method achieves a root mean square localization error of less than 0.3 m in UWB experiments.
- It significantly improves localization accuracy and ensures continuous tracking in NLOS conditions.
- Compared to conventional methods, the new approach offers better performance in dynamic radio environments.

## Abstract

Localization is one of the essential problems in the Internet of Things (IoT). Dynamic changes in the radio environment may lead to poor localization accuracy or discontinuous localization in non-line-of-sight (NLOS) scenarios. To address this problem, this paper proposes a localization enhancement method based on direct-path identification and tracking. More specifically, the proposed method significantly reduces the range error and localization error by quickly identifying the line-of-sight (LOS) to NLOS transition and effectively tracking the direct path. In a large testing hall, localization experiments based on the ultra-wideband (UWB) signal have been carried out. Experimental results show that the proposed method achieves a root mean square localization error of less than 0.3 m along the user equipment (UE) movement trajectory with serious NLOS propagation conditions. Compared with conventional methods, the proposed method significantly improves localization accuracy while ensuring continuous localization.