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