Multi-Modal Probabilistic Indoor Localization on a Smartphone

Co-authors

Frederike Dümbgen, Cynthia Oeschger, Mihailo Kolundzija, Emmanuel Girardin, Johan Leuenberger and Serge Ayer.


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Full text: Infoscience.
Cite: .
Code: Will appear shortly.


Abstract

The satellite-based Global Positioning System (GPS) provides robust localization on smartphones outdoors. In indoor en- vironments, however, no system is close to achieving a similar level of ubiquity, with existing solutions offering different trade-offs in terms of accuracy, robustness and cost.

In this paper, we develop a multi-modal positioning system, targeted at

Bound and conquer: Improving triangulation by enforcing consistency

Co-authors

Alireza Ghasemi and Martin Vetterli.


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Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Code ocean.


Abstract

We study the accuracy of triangulation in multi-camera systems with respect to the number of cameras. We show that, under certain conditions, the optimal achievable reconstruction error decays quadratically as more cameras are added to the system. Furthermore, we analyse the error decay-rate of major state-of-the-art algorithms with

Combining Range and Direction for Improved Localization

Co-authors

Gilles Baechler, Frederike Dümbgen, Golnoosh Elhami, Miranda Krekovic, Robin Scheibler and Martin Vetterli.


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Full text: Infoscience.
Cite: Bibtex.
Code: GitHub.


Abstract

Self-localization of nodes in a sensor network is typically achieved using either range or direction measurements; in this paper, we show that a constructive combination of both improves the estimation. We propose two localization algorithms that make use of the differences between the sensors’

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