Title: Reduced Multipath Channel Modelling Preserving Representative GNSS Receiver Testing
Author(s): F. Ribaud, M. Ait-Ighil, S. Rougerie, J. Lemorton, O. Julien, F. Pérez-Fontan
Published in: Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016)
September 12 - 16, 2016
Oregon Convention Center
Portland, Oregon
Pages: 295 - 303
Cite this article: Ribaud, F., Ait-Ighil, M., Rougerie, S., Lemorton, J., Julien, O., Pérez-Fontan, F., "Reduced Multipath Channel Modelling Preserving Representative GNSS Receiver Testing," Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 295-303.
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Abstract: The focus of this paper is the multipath channel reduction problem for GNSS receiver’s performances assessment, which means quantifying the impact of the signal echoes on the new GNSS receivers depending on the environment they are going through. Because of the hardware signal emulation limitations, the number of discrete multipaths in the modelled impulse responses samples has to be decreased to less than 10 units. Three different reduction methods have been implemented and applied to the same impulse response snapshots. They are issued from various approaches of the channel reduction techniques and aim at covering the whole field of possibilities to address this problem. The first reduction approach consists in the aggregation of groups of multipaths, according to different proximity criterions. An optimal aggregation method has been developed aiming at preserving the channel delay and Doppler characteristics at best. The second approach aims at parametrizing the reduced channel multipaths to optimize the preservation of the channel autocorrelation function. The iterative Expectation-Maximization algorithm SAGE has been used to optimize the multipaths delay, Doppler, Power and phase to optimize the similarity between the channel autocorrelation function before and after the reduction process. The last approach considers the parameters of the reduced channel multipaths as the realization of a stochastic process. Therefore, these parameters are drawn from statistical distributions and transition probability matrix. Those 3 methods are finally compared through the comparison of their respective preservation of the GNSS receiver’s pseudo-range error performances, along a trajectory in a virtual city reproducing classic urban scenarios. Both discriminator error and DLL dynamic tracking loop error are investigated to assess the performances of the different methods in terms of receiver’s positioning preservation.