A Composite Model for Indoor GNSS Signals: Characterization, Experimental Validation and Simulation

Shashank Satyanarayana, Daniele Borio and Gerard Lachapelle

Peer Reviewed

Abstract: In this paper, the problem of characterizing and simulating indoor Global Navigation Satellite Systems (GNSS) signals is addressed. A detailed methodology for characterizing the temporal/spatial behavior of indoor GNSS signal amplitude is first presented. The proposed methodology is then used to extract the signal amplitude and its empirical Probability Density Function is compared against several standard distributions. From the analysis, it emerges that the slow and fast fading components affecting received GNSS signals need to be modeled separately. In this respect, a composite Rice/Log-Normal model able to effectively capture the behavior of the indoor signal amplitude is considered. Several experiments have been conducted and the validity of the composite model has been validated against measurements. It is shown that the spectra of the slow and fast fading components can be effectively modeled using a fourth order low-pass Butterworth filter. A simulation scheme is finally suggested for the generation of indoor GNSS signals.
Published in: NAVIGATION: Journal of the Institute of Navigation, Volume 59, Number 2
Pages: 77 - 92
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