Abstract
This paper is devoted to methods for localizing individual sensor nodes connected in a network. The novelty of the proposed method is the model-based approach (i.e., rigorous exploitation of physical background knowledge) using local observations of a distributed phenomenon. By exploiting background phenomena, the individual sensor nodes can be localized by only locally measuring their surrounding without the necessity of heavy infrastructure. Two approaches are introduced: (a) the polynomial system localization method and (b) the simultaneous reconstruction and localization method. The first approach (PSL-method) is based on restating the mathematical model of the distributed phenomenon in terms of a polynomial system. Solving the system of polynomials for each individual sensor node directly leads to the desired locations. The second approach (SRL-method) regards the localization problem as a simultaneous state and parameter estimation problem within a Bayesian framework. By this means, the distributed phenomenon is reconstructed and the individual nodes are localized in a simultaneous fashion, while considering remaining stochastic uncertainties.
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Sawo, F., Henderson, T.C., Sikorski, C., Hanebeck, U.D. (2009). Passive Localization Methods Exploiting Models of Distributed Natural Phenomena. In: Hahn, H., Ko, H., Lee, S. (eds) Multisensor Fusion and Integration for Intelligent Systems. Lecture Notes in Electrical Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89859-7_26
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