Radio-frequency identification (RFID) plays a large role in today’s logistics. Relatively narrowband signals are used to identify goods. However, it is difficult to find out where those goods are using RFID. As the image shows, the power of the received signal shows huge variations, even inside a special RFID readout zone. In a typical application area, such as a large warehouse, this makes accurate localization using standard RFID almost impossible.

In a joint project with TU Vienna and industrial partners, we address this issue by developing novel localization methods for RFID systems. In particular, a novel distance estimation method will be implemented and tested. The aim of this thesis is to implement this novel method into an existing RFID simulation framwork (PARIS), which has been developed in a previous project at our lab [1], [2]. Using this simulator, enhanced position estimation algorithms can then be developed.

Your Tasks

• Get used to the PARIS simulation framework using [1], [2]
• Extend PARIS by new distance estimation methods
• Investigate enhanced position estimation algorithms

Requirements

• Interest in wireless communications and signal processing
• Matlab programming skills (The PARIS framework is a Matlab tool)
• Mobile Radio Systems beneficial

References

[1] Arnitz, D.; “Tag Localization in Passive UHF RFID”, 2011, Dissertation, Graz University of Technology, Austria.

[2] Arnitz, D.; “PARIS Simulation framework”, Open-source simulator, https://www.spsc.tugraz.at/tools/paris-osf