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WiFi localization and tracking of indoor moving objects is an important problem in many contexts of ubiquitous buildings, first responder environments, and others. Previous approaches in WiFi-based indoor localization and tracking either assume prior knowledge of indoor environment or assume many data samples from location-fixed WiFi sources (i.e. Anchor points). However, such assumptions are not always true, especially in emergency scenarios. This paper explores the possibility of real-time indoor localization and tracking without any knowledge of indoor environment and with real time data samples from only few anchor points outside the building.
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