A particle filtering tracking algorithm for GNSS synchronization using Laplace's method

Multipath is one of the dominant sources of error in high- precision GNSS applications. A tracking algorithm is presented that explicitely accounts for direct signal and multipath replicas in the model, in order to mitigate the contributions of the latter. A Bayesian approach has been taken, to infe...

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Bibliographic Details
Published in2008 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 3409 - 3412
Main Authors Closas, P., Ferndndez-Prades, C., Ferndndez-Rubio, J.A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2008
Subjects
Additive white noise
Delay effects
Delay estimation
Electronic mail
Filtering algorithms
Gaussian noise
Global Positioning System
Monte Carlo methods
Multipath channels
Particle tracking
Satellite navigation systems
Tracking
Tracking loops
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Summary:Multipath is one of the dominant sources of error in high- precision GNSS applications. A tracking algorithm is presented that explicitely accounts for direct signal and multipath replicas in the model, in order to mitigate the contributions of the latter. A Bayesian approach has been taken, to infer some information from the time evolution model of the parameters. Due to the nonlinearity of the measurement model, a Particle Filtering algorithm has been designed. The proposed PF considers Rao-Blackwellization with a CKF and the selection of the importance density is performed via the use of Laplace's method, which yields to an importance density close the optimal. Simulations compare performance to EKF and PCRB.
ISBN:9781424414833
1424414830
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2008.4518383