Entity Localization and Tracking: A Sensor Fusion-based Mechanism in WSNs

Abstract : Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables; nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.
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Stefano Tennina, Marco Valleta, Fortunato Santucci, Marco Di Renzo, Fabio Graziosi, et al.. Entity Localization and Tracking: A Sensor Fusion-based Mechanism in WSNs. IEEE MELT-11, Sep 2011, Banff, Canada. pp.1-6. ⟨hal-00663057⟩

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