Quantification of the multipath-induced error in GNSS code-based range measurements is usually entrusted to curves as the multipath error envelope (MEE). Although very useful for comparative evaluations, these metrics do not include any realistic information on the propagation channel statistical characterization and consequently cannot be used to quantify the multipath error in an absolute way. A modification of the MEE is therefore proposed, including semi-analytic realizations of the channel statistics, in the form of the power-delay profile and the delays distribution. In addition, the multipath error distribution and the multipath error probability are derived, leading to a realistic evaluation of the performance of different discriminator architectures in different scenarios.
Evaluation of the Multipath-induced Error Probability on the Estimation of Code-based Pseudoranges / Falletti, Emanuela; Linty, NICOLA UMBERTO. - ELETTRONICO. - (2012), pp. 1-8. (Intervento presentato al convegno 6th ESA Workshop on Satellite Navigation Technologies (Navitec 2012) & European Workshop on GNSS Signals and Signal Processing tenutosi a Noordwijk, The Netherlands nel December 5-7, 2012) [10.1109/NAVITEC.2012.6423082].
Evaluation of the Multipath-induced Error Probability on the Estimation of Code-based Pseudoranges
FALLETTI, EMANUELA;LINTY, NICOLA UMBERTO
2012
Abstract
Quantification of the multipath-induced error in GNSS code-based range measurements is usually entrusted to curves as the multipath error envelope (MEE). Although very useful for comparative evaluations, these metrics do not include any realistic information on the propagation channel statistical characterization and consequently cannot be used to quantify the multipath error in an absolute way. A modification of the MEE is therefore proposed, including semi-analytic realizations of the channel statistics, in the form of the power-delay profile and the delays distribution. In addition, the multipath error distribution and the multipath error probability are derived, leading to a realistic evaluation of the performance of different discriminator architectures in different scenarios.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2520116
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