Neural network based path detection for an FMCW positioning system

Authors:
Ralf Mosshammer;Florian Frank;Mario Huemer
Affiliations:
Institute for Electronics Engineering, University of Erlangen-Nuremberg, Erlangen, Germany;Institute for Electronics Engineering, University of Erlangen-Nuremberg, Erlangen, Germany;Embedded Systems, NES, Klagenfurt University, Klagenfurt, Austria
Venue:
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
Year:
2007

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Abstract

Multipath propagation is a major source of error for runtime detection based positioning systems. For the case of an FMCW-based positioning system, the overlap of pulse shapes in the frequency domain restricts exact measurement of frequency, and thus of runtime. Choosing a measurement point on the slope of the pulse is a way to mitigate measurement errors. In this paper, we present a neural network as a means of estimating the ideal measurement point. The network is shown to outperform fixed level measurements even with very sparse training data.