Calibration of Wi-Fi-Based Indoor Tracking Systems for Android-Based Smartphones

Abstract

With the growing development of smartphones equipped with Wi-Fi technology and the need of inexpensive indoor location systems, many researchers are focusing their efforts on the development of Wi-Fi-based indoor localization methods. However, due to the difficulties in characterizing the Wi-Fi radio signal propagation in such environments, the development of universal indoor localization mechanisms is still an open issue. In this paper, we focus on the calibration of Wi-Fi-based indoor tracking systems to be used by smartphones. The primary goal is to build an accurate and robust Wi-Fi signal propagation representation in indoor scenarios.We analyze the suitability of our approach in a smartphone-based indoor tracking system by introducing a novel in-motion calibration methodology using three different signal propagation characterizations supplemented with a particle filter. We compare the results obtained with each one of the three characterization in-motion calibration methodologies and those obtained using a static calibration approach, in a real-world scenario. Based on our experimental results, we show that the use of an in-motion calibration mechanism considerably improves the tracking accuracy.

Keywords

• RSSI-based
• particle filter
• in-motion calibration
• smartphone tracking
• path loss model