LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning

Area of Science:

• Computer Science
• Electrical Engineering
• Robotics

Background:

• Indoor positioning systems (IPS) face challenges in accuracy, especially in complex environments.
• Infrastructure-free solutions are sought to avoid specialized hardware.
• Fingerprinting, a popular method, requires extensive calibration and updates.

Purpose of the Study:

• To present a novel, calibration-free indoor localization approach named LOCALI.
• To overcome the limitations of traditional fingerprinting methods in terms of effort and accuracy.
• To enhance indoor positioning by leveraging environmental map information.

Main Methods:

• Developed a systematic localization approach (LOCALI) that utilizes floor plans/wall maps.
• Generated radio maps by integrating path-losses over trajectories.
• Estimated target position by integrating path-loss data with map information, avoiding signal strength triangulation issues.

Main Results:

• LOCALI achieves significant indoor positioning accuracy by integrating map information and environmental parameters.
• The system effectively generates radio maps without requiring a pre-existing calibration database.
• Demonstrated reduced effort compared to calibration-based indoor positioning techniques.

Conclusions:

• The LOCALI approach offers a viable and less laborious alternative for infrastructure-free indoor positioning.
• Leveraging environmental maps and path-loss integration enhances localization accuracy in challenging indoor settings.
• This method addresses the limitations of fingerprinting, paving the way for wider adoption of indoor positioning.