Effortless 3D radio maps generation for fingerprinting-based indoor positioning system

Area of Science:

• Computer Science
• Electrical Engineering
• Geospatial Science

Background:

• Indoor Positioning Systems (IPS) are crucial for location-based services in complex environments like malls and hospitals.
• Traditional fingerprinting techniques for IPS are labor-intensive and costly due to manual database calibration.
• Existing automated methods often overlook crucial height (z-axis) information, limiting accuracy.

Purpose of the Study:

• To develop a systematic approach for estimating indoor user/object locations using 3D path loss heat maps.
• To overcome the limitations of 2D-based methods by incorporating height parameters for more precise positioning.
• To reduce the cost and effort associated with generating fingerprinting databases for IPS.

Main Methods:

• Generation of 3D path loss heat maps incorporating Received Signal Strength (RSS) values and height parameters.
• Systematic approach for indoor location estimation utilizing the generated 3D heat maps.
• Experimental validation comparing the proposed 3D method against manual and existing 2D techniques.

Main Results:

• The proposed 3D path loss technique significantly outperforms manual and existing 2D methods in accuracy.
• Achieved 1-meter error in 20% of cases and 2-meter error in 40% of cases.
• 3D heat maps were generated with reduced effort compared to manual data collection, demonstrating improved accuracy.

Conclusions:

• The 3D path loss heat map approach offers a more accurate and cost-effective solution for indoor positioning.
• Incorporating height information is vital for enhancing the precision of indoor navigation systems.
• The proposed method improves the adaptability and efficiency of fingerprinting-based IPS.