Measurement-Guided Ray Tracing: Estimation of Propagation Paths Based on Spatiotemporal Measurement Data of User-Induced Fading of Multipath Components

Martin Schmidhammer, Christian Gentner, Benjamin Siebler, and Stephan Sand

Abstract: In this paper, we introduce a novel measurement-guided ray tracing approach for estimating the location of reflection points (RPs) arising from single-bounce reflections. This method is independent of any prior environmental information, such as floor plans. Instead, it formulates an optimization problem that aligns the parameters of an empirical fading model with time-series data of user-induced power changes. This approach not only estimates the location of the RP but also provides estimates of the underlying model parameters. The effectiveness of the proposed method is demonstrated through its application to ultra-wideband measurement data within an indoor environment. Our results indicate that the approach delivers highly accurate estimates of the RP location, with only negligible deviations from the true propagation paths. A qualitative comparison between the modeled power changes and the actual measured time-series data reveals a strong agreement, which underlines the robustness and applicability of the proposed method. This validation confirms that the approach effectively estimates both the model parameters and the RPs location, offering a reliable solution for scenarios where prior environmental information is unavailable.
Published in: Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024)
September 16 - 20, 2024
Hilton Baltimore Inner Harbor
Baltimore, Maryland
Pages: 1484 - 1490
Cite this article: Schmidhammer, Martin, Gentner, Christian, Siebler, Benjamin, Sand, Stephan, "Measurement-Guided Ray Tracing: Estimation of Propagation Paths Based on Spatiotemporal Measurement Data of User-Induced Fading of Multipath Components," Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024), Baltimore, Maryland, September 2024, pp. 1484-1490. https://doi.org/10.33012/2024.19813
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