Talks and Poster Presentations (with Proceedings-Entry):

M. Thienelt, A. Eichhorn, A. Reiterer:
"Pedestrian Positioning with Kalman-Filter and Knowledge-Based Analysis";
Poster: International Conference on Optical 3-D Measurement Techniques VIII, Zürich; 2007-07-09 - 2007-07-12; in: "Optical 3-D Measurement Techniques VIII", A. Grün, H. Kahmen (ed.); Volume II (2007), ISBN: 3-906467-67-8; 248 - 255.

English abstract:
In this paper the prototype of a map-independent knowledge-based Kalman filter (`WiKaF´) for
optimal pedestrian positioning is presented. The WiKaF concept, its system architecture and the
integrated sensors are described. The multi-sensor system comes from the NAVIO project (another
project for pedestrian navigation in Vienna) and contains a Dead Reckoning Module DRM III, a
barometer PTB 220, a digital compass HMR 3000 and an eTrex Summit GPS receiver. The two
main components of the position module are introduced. At the present time the knowledge-based
component is responsible for the pre-filtering process of the measurement data which includes a
first step of outlier detection. In a further step the central Kalman filter derives the optimal position
of the pedestrian. For support in dead reckoning scenarios the filters system equations connect the
multi-sensor output with a causal motion model. The combination of knowledge-based component
and Kalman filtering preliminary aims at an increasing reliability of the filter.

Created from the Publication Database of the Vienna University of Technology.