TU BRAUNSCHWEIG
| Carl-Friedrich-Gauß-Fakultät | Informatik
Informatikzentrum

Statistical approach for the InPhase positioning system

Bearbeiter (anonym, Login erforderlich)
Betreuer Yannic Schröder
Georg von Zengen
Stephan Rottmann
Professor Prof. Dr.-Ing. Lars Wolf
Projekt inga
IBR Gruppe CM (Prof. Wolf)
Art Bachelorarbeit
Status abgeschlossen
Beginn 29.06.2015

Einleitung

It is often very important to be able to know the position of objects or persons. As far as the outdoor is concerned, global navigation systems based on satellites, such as GPS, have performed very well for years. As for the indoor scenarios, no final or satisfactory solution has been found yet. Although many solutions have been put forward, in fact, none of them could cope with all the possible indoor scenarios because each indoor scenario presents specific characteristics: the wall distribution, width and construction materials, the radio frequencies used, possible interferences, etc. The technological developments in wireless communication, sensors and micro controllers have allowed further research on this matter, in order to create, through inexpensive methods, effective positioning systems with a low energy cost. It is easier to get thanks to the Wireless Sensor Networks (WSN) technology.

Aufgabenstellung

The aim of this thesis is to find a statistical solution to reduce the limitations of the location problem. Such a solution could be represented as probabilistic maps. Probabilistic maps could be treated in the same way as black and white digital images. If for black and white digital images there is a two-dimensional matrix, the values of which represent the grey scale of each pixel, for probabilistic maps the values would indicate the probability of the tag occupying a certain position. Assuming that, the same approach used in treating digital images could provide better solutions to the location problem. However, this is not the main goal of this thesis, but rather a useful tool in terms of its scope.

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aktualisiert am 05.11.2015, 15:02 von Yannic Schröder
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