At the 12th International Conference on Indoor Positioning and Indoor Navigation in Beijing/China in early September 2022, transport and traffic scientists from the Chair of Transport Systems Information Technology at the "Friedrich List" Faculty of Transport and Traffic Sciences were invited to present their own research topics and results. 

The head of the chair, Prof. Oliver Michler, and two of his research assistants, Andrea Jung and Paul Schwarzbach, were represented by name. The paper entitled "Auto-Positioning in Radio-based Localization Systems: A Bayesian Approach" was presented by Jung.

The goal of the research discussed in the paper was to develop a discrete Bayesian approach to solving robust autopositioning compared to conventional closed-form methods for non-stationary and unknown network configurations. At the same time, the aim is to reduce the requirements for connectivity and availability of usable distance measurements. The method was validated using real data from the near static environment.

Specifically, various multi-path, outlier and interfering distance measurements were performed. Using this approach, a 58 per cent increase in positioning accuracy can be achieved compared to a basic closed-loop approach to automated positioning.