Software based solutions for mobile positioning

Hamani, Sadek (2013). Software based solutions for mobile positioning. University of Birmingham. Ph.D.

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Abstract

This thesis is concerned with the development of pure software-based solutions for cellular positioning. The proposed self-positioning solutions rely solely on the available network infrastructure and do not require additional hardware or any modifications in the cellular network. The main advantage of using RSS rather than timing measurements is to overcome the need for synchronisation between base stations. By exploiting the availability of RSS observations, the self-positioning methods presented in this thesis have been implemented as mobile software applications and tested in real world positioning experiments. The well-known Extended Kalman Filter can be used as a static positioning process while modeling the uncertainty in signal strength observations. The range estimation is performed using an empirical propagation model that has been calibrated using RSS measurements in the same trial areas where the positioning process is applied. In order to overcome the need for a priori maps of the GSM network, a novel cellular positioning method is proposed in this thesis. It is based on the concept of Simultaneous Localisation And Mapping (SLAM) which represents one of the greatest successes of autonomous navigation research. By merging target localisation and the mapping of unknown base stations into a single problem, Cellular SLAM allows a mobile phone to build a map of its environment and concurrently use this map to determine its position.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):