Multi-AP and Test Point Accuracy of the Results in WiFi Indoor Localization

Area of Science:

• Engineering
• Computer Science
• Signal Processing

Background:

• WiFi-based indoor positioning is crucial for many applications.
• Existing Angle-of-Arrival (AoA) algorithms like MUSIC have limitations in complex environments.
• Factors influencing indoor localization accuracy require deeper investigation.

Purpose of the Study:

• To identify and analyze factors affecting WiFi indoor localization accuracy.
• To develop and implement an improved joint localization algorithm.
• To evaluate the performance of the new algorithm against existing methods.

Main Methods:

• Experimental assessment of Test Point (TP) accuracy in a 290 m2, three-room environment with three Access Points (APs).
• Implementation of a novel algorithm for joint localization using multiple APs.
• Statistical analysis of localization errors, considering space-dependent factors.

Main Results:

• Local space-dependent factors, including distance, obstacles, and corner locations, are identified as primary error sources.
• The developed joint localization algorithm achieved a 46% mean accuracy improvement over the SpotFi algorithm.
• Unbiased joint localization showed a 20% median accuracy improvement compared to individual localization.

Conclusions:

• Environmental factors critically influence WiFi indoor positioning accuracy.
• The proposed joint localization algorithm significantly enhances positioning precision in complex indoor settings.
• Further research into mitigating environmental impacts is recommended for robust indoor positioning systems.