High-accuracy positioning is a capability that has been enabling a vast number of applications. With increasing capabilities of positioning systems, which nowadays extend from “classical” navigation satellite systems and inertial navigation solutions to systems based on wireless communications standards and other “signals of opportunity”, position information continues to become available to more and more challenging applications. Autonomous driving and driver-assistance systems are among the use cases, where the availability of reliable position infomation is considered to be “mission critical”.

This student project or master thesis project is concerned with advanced systems for vehicle positioning. A range of signal processing methods have been developed by members of the SPSC lab in recent years for indoor applications. The goal of this project is to migrate these existing algorithms to vehicular environments. The student will collect a set of measurements using RF equipment available at the SPSC lab, analyze those data, and use the data to validate positioning and position tracking algorithms in a realistic but controlled setting. The work will be conducted in the framework of a collaboration with MAGNA Steyr Engineering, Graz; the supervision of the project will be conducted by members of the SPSC lab.

Your profile: Attendance to the courses ‘Statistical signal processing’ and/or ‘Computational intelligence’ as well as some basic MATLAB skills are beneficial but not required.

(A note on language: all projects can be conducted in German or English!)

References:

K. Witrisal, P. Meissner, E. Leitinger, Y. Shen, C. Gustafson, F. Tufvesson, K. Haneda, D. Dardari, A. Molisch, A. Conti and M. Z. Win, “High-Accuracy Localization for Assisted Living: 5G systems will turn multipath channels from foe to friend,” _IEEE Signal Processing Mag.,_vol. 33, no. 2, pp. 59-70, March 2016.

Die Presse, “Punktgenaue Ortung im Gebäude”, Jan. 9, 2016