Multipath Characterization Using Ray-Tracing in Urban Trenches

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Abstract

Multipath in urban environments still represents a great challenge for Global Navigation Satellite System (GNSS) positioning as it is a degrading factor which limits the attainable accuracy, precision and integrity. In an urban trench, the dense building structures in the vicinity of the antenna cause reflections of the satellite signals resulting in multipath errors. Various work has been presented for simulating reflections for stations under laboratory conditions, yet the simulative analysis of multipath propagation in urban environments is currently developing. In this contribution, we enhanced an existing Ray-Tracing algorithm which identifies potentially multipath affected satellite signals. So far, it calculates reflection points on a plane ground and estimates the resulting multipath error. We extended it for the urban area case by introducing a 3D city building model with possible reflections on all surfaces of the buildings. Based on the geometry between the antenna position, satellite position and the reflection surface, the extra path delays, the characteristics of the propagation channel and the signal amplitudes are calculated. The resulting multipath errors are then estimated from the discriminator function using state of the art correlator parameters and antenna models. For a validation, the simulation results are compared with code-minus-carrier combination from a real GNSS experiment in a dense urban area in Hannover. We find that the simulated multipath errors fit the observations in terms of the amplitude, but with uncertainties in the building model, the multipath wave length is too large. The distance to the reflection surface is a key factor which influences the multipath wavelength.

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APA

Icking, L., Ruwisch, F., & Schön, S. (2023). Multipath Characterization Using Ray-Tracing in Urban Trenches. In International Association of Geodesy Symposia (Vol. 154, pp. 359–365). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/1345_2022_166

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