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Nonlinear Bayesian Tracking Loops for Multipath Mitigation
Author(s) -
Pau Closas,
Carles Fernández–Prades,
José Raúl Fernández del Castillo Díez,
David Castro
Publication year - 2012
Publication title -
international journal of navigation and observation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.176
H-Index - 18
eISSN - 1687-6008
pISSN - 1687-5990
DOI - 10.1155/2012/359128
Subject(s) - gnss applications , multipath propagation , computer science , particle filter , context (archaeology) , nonlinear system , bayesian probability , tracking (education) , filter (signal processing) , control theory (sociology) , channel (broadcasting) , kalman filter , electronic engineering , engineering , telecommunications , global positioning system , artificial intelligence , physics , computer vision , paleontology , pedagogy , control (management) , quantum mechanics , biology , psychology
This paper studies Bayesian filtering techniques applied to the design of advanced delay tracking loops in GNSS receivers with multipath mitigation capabilities. The analysis includes tradeoff among realistic propagation channel models and the use of a realistic simulation framework. After establishing the mathematical framework for the design and analysis of tracking loops in the context of GNSS receivers, we propose a filtering technique that implements Rao-Blackwellization of linear states and a particle filter for the nonlinear partition and compare it to traditional delay lock loop/phase lock loop-based schemes

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