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Published in:
2009 | OriginalPaper | Chapter
On Structural Identification of 2D Regression Functions for Indoor Bluetooth Localization
Authors : Rene Mayrhofer, Stephan Winkler, Helmut Hlavacs, Michael Affenzeller, Stefan Schneider
Published in: Computer Aided Systems Theory - EUROCAST 2009
Publisher: Springer Berlin Heidelberg
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In-door localization of mobile devices is a common problem for many current and future applications, for example to control infrastructure services or for personalized in-building navigation systems. Sufficiently capable Bluetooth support is often available in off-the-shelf mobile devices such as mobile phones, which makes Bluetooth an attractive technology for cheap and widely available in-door localization systems. However, Bluetooth has been optimized to deal with effects of radio frequency transmission such as reflection and multi-path propagation. It therefore produces highly non-linear relationships between the distance of devices and their perceived signal strength. In this paper, we aim to identify these relationships for a specific dataset of 2D device positions using structural identification methods. Driven by an extended genetic algorithm, we aim to find optimal mappings in form of non-linear equations for
x
and
y
coordinates, thus producing formal regression functions.