Multipath Mitigation in Global Navigation Satellite Systems Using a Bayesian Hierarchical Model with Bernoulli Laplacian Priors - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Multipath Mitigation in Global Navigation Satellite Systems Using a Bayesian Hierarchical Model with Bernoulli Laplacian Priors

Résumé

A new sparse estimation method was recently introduced in a pre-vious work to correct biases due to multipath (MP) in GNSS me-asurements. The proposed strategy was based on the resolution ofa LASSO problem constructed from the navigation equations usingthe reweighted-`1method. This strategy requires to adjust the re-gularization parameters balancing the data fidelity term and the in-volved regularizations. This paper introduces a new Bayesian es-timation method allowing the MP biases and the unknown modelparameters and hyperparameters to be estimated directly from theGNSS measurements. The proposed method is based on Bernoulli-Laplacian priors, promoting sparsity of MP biases.
Fichier principal
Vignette du fichier
Lesouple_20172.pdf (485.06 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02983154 , version 1 (02-11-2020)

Identifiants

Citer

Julien Lesouple, Jean-Yves Tourneret, Mohamed Sahmoudi, Franck Barbiero, Frédéric Faurie. Multipath Mitigation in Global Navigation Satellite Systems Using a Bayesian Hierarchical Model with Bernoulli Laplacian Priors. IEEE Workshop on Statistical Signal Processing (SSP 2018), Jun 2018, Freiburg, Germany. ⟨10.1109/SSP.2018.8450818⟩. ⟨hal-02983154⟩
43 Consultations
33 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More