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Beschreibung:
In wireless propagation transmitted signals are reflected, scattered and diffracted by objects. Especially in urban canyons or inside buildings, the signal reaching the receiving antenna consists of multiple replicas of the transmitted signal, which are called multipath components. The positioning accuracy might be drastically reduced due to the distorted received signal by multipath components. Hence, positioning algorithms need to mitigate the impact of multipath components on the received signal to obtain an accurate position estimate. With this thesis, we propose a paradigm shift in how to process the received signal in order to provide accurate position estimation for mobile receivers: rather than mitigating multipath components we propose an algorithm to exploit multipath. We call this algorithm Channel-SLAM. The basic idea of Channel-SLAM is to interpret multipath components as signals emitted from so called virtual transmitters. These virtual transmitters are inherently time synchronized to the physical transmitter and static in their positions. In this thesis, we show that the presence of multipath components allows positioning even if signals of only one physical transmitter are receivable. The concept of virtual transmitters considers multipath propagation occurring due to multiple numbers of reflections, diffractions or scattering as well as the combination of these effects. Specifically, we derive a generic signal model to describe virtual transmitters, where a distinct model detection for reflection, diffraction or scattering is not necessary. To use the information of the multipath components, Channel-SLAM estimates the position of the virtual transmitters without the necessity of any prior information such as a room-layout. The novelty of the algorithm is to estimate the position of the receiver and the virtual transmitters simultaneously, which can be interpreted as simultaneous localization and mapping (SLAM) with radio signals. Instead of mapping the physical environment, Channel-SLAM maps the ...