A Novel Robust Trilateration Method Applied to Ultra-Wide Bandwidth Location Systems

Area of Science:

• Wireless communication
• Localization algorithms
• Signal processing

Background:

• Range-based localization methods struggle with non-line-of-sight (NLOS) and multipath fading (MPF) in wireless networks.
• Conventional trilateration methods, like centroid-based and least squares, often fail due to the non-existence of intersection points.

Purpose of the Study:

• To propose a novel confidence-based intersection method to enhance localization accuracy and robustness.
• To address the challenge of non-existent intersection points in NLOS and MPF environments.

Main Methods:

• A confidence interval is estimated using the Cramér-Rao lower bound of time-of-flight (TOF) measurements.
• The method expands the range of circles within this confidence interval.
• An intersection determination algorithm selects the point with the highest confidence level.

Main Results:

• The proposed method significantly improves localization accuracy compared to conventional trilateration.
• It demonstrates superior robustness to noise in wireless network environments.
• Simulation and experimental results validate the effectiveness of the confidence-based approach.

Conclusions:

• The confidence-based intersection method effectively overcomes the limitations of traditional trilateration in challenging wireless channels.
• This approach offers a more reliable solution for accurate positioning in NLOS and MPF conditions.
• The method enhances the practical applicability of range-based localization in real-world wireless networks.