Optimization of a Time-of-Arrival-Ridge Estimation Iterative Model for Ultra-Wideband Positioning in a Long Linear...

Area of Science:

• Engineering
• Computer Science
• Signal Processing

Background:

• Ultra-wideband (UWB) technology offers high-precision indoor positioning but struggles in environments with linear base station deployment.
• Structural constraints in long linear areas like tunnels and corridors degrade UWB localization accuracy, making conventional algorithms ineffective.

Purpose of the Study:

• To develop a high-precision Ultra-wideband (UWB) positioning algorithm for accurate localization in long linear environments.
• To address the limitations of existing UWB localization methods in scenarios with near-linear base station arrangements.

Main Methods:

• Proposed a novel UWB+TOA-R positioning algorithm integrating Ridge estimation as a constraint.
• Developed an iteratively computed Time of Arrival-Ridge estimation iterative (TOA-RR) solution model with refined iterative computations.
• Compared the performance of TOA-Least Squares (TOA-LS), TOA-Ridge estimation (TOA-R), and the proposed TOA-RR models in a long linear corridor.

Main Results:

• The TOA-LS model exhibited significant coordinate distortions due to coefficient matrix abnormalities.
• The TOA-R model showed improved accuracy and stability but retained residual errors.
• The proposed TOA-RR model achieved enhanced stability and accuracy, with a positioning error of approximately 0.5 meters.

Conclusions:

• The TOA-RR algorithm effectively resolves the challenge of inaccurate UWB localization in long linear areas.
• The proposed method provides a robust and accurate solution for UWB positioning in constrained linear environments.
• This research offers a significant advancement for UWB applications in tunnels, corridors, and similar settings.