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

Area of Science:

• Wireless communication
• Internet of Things (IoT)
• Localization and positioning

Background:

• Accurate localization is critical for Internet of Things (IoT) applications.
• Dynamic radio environments and non-line-of-sight (NLOS) propagation degrade localization accuracy and continuity.

Purpose of the Study:

• To develop and validate a novel localization enhancement method for IoT devices.
• To address the challenges posed by NLOS propagation and radio environment dynamics.

Main Methods:

• Proposed a method for direct-path identification and tracking.
• Implemented line-of-sight (LOS) to NLOS transition identification.
• Utilized ultra-wideband (UWB) signals for experimental validation.

Main Results:

• Achieved a root mean square localization error below 0.3 m in extensive tests.
• Demonstrated significant reduction in range and localization errors.
• Successfully maintained continuous localization under severe NLOS conditions.

Conclusions:

• The proposed method substantially enhances localization accuracy in challenging IoT environments.
• Effective direct-path tracking overcomes NLOS propagation issues.
• The approach ensures reliable and continuous localization for moving user equipment (UE).