Distributive target tracking in sensor networks with a Markov random field model
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
FM radio for indoor localization with spontaneous recalibration
Pervasive and Mobile Computing
Perspectives on Cognitive Computing and Applications
International Journal of Software Science and Computational Intelligence
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Wireless sensor network (WSN) is widely used in many applications such as localization and real-time tracking system. Previous researches commonly suffer the line-of-sight (LOS) problem and dependence on contrast of the background light intensity. Location Fingerprinting (LF) method uses a training dataset of received signal strength (RSS) at different location to track the target. The drawbacks of LF method are needed to have extensive training dataset surveying and highly affected by the changing of internal building infrastructure. In this paper, a sensor-based LF method will be implemented to replace extensive site-surveying. Using a Kalman Filter tracks multiple points to characterize a trajectory. Our experimental result shows that the effectiveness of our method leads to have more accurate and effective tracking system.