| Carl Friedrich Gauß Faculty | Department of Computer Science

Statistical approach for the InPhase positioning system

Student(anonymous, Login required)
SupervisorYannic Schröder
Dr. Georg von Zengen
Stephan Rottmann
ProfessorProf. Dr.-Ing. Lars Wolf
IBR GroupCM (Prof. Wolf)
TypeBachelor Thesis


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.


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.


last changed 2018-10-02, 13:09 by Yannic Schröder