Accéder directement au contenu Accéder directement à la navigation
Communication dans un congrès

GPS/GLONASS Data Fusion and Outlier Elimination to Improve the Position Accuracy of Receiver

Ngoc Tan Truong 1 Ali Khenchaf 1 Fabrice Comblet 1 Pierre Franck 2 Jean-Marc Champeyroux 2 Olivier Reichert 2
1 Lab-STICC_ENSTAB_MOM_PIM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : To improve the accuracy of receiver's positions, Global Navigation Satellite System (GNSS) brings more signals and more satellites. This paper presents data fusion from multiple satellite constellations. Indeed, multiple satellite failures impact the determination of the user position and should be considered. For this purpose, the present paper provides a robust estimation to detect and exclude multi-faults. This paper presents a robust MM class estimator for the GNSS positioning using data from the GLONASS and combination with GPS data. The results are improved by up to 70.96% with the position fusion and the robust estimation algorithm compared with using GPS data only.
Type de document :
Communication dans un congrès
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-02457678
Contributeur : Marie Briec <>
Soumis le : mardi 28 janvier 2020 - 11:39:53
Dernière modification le : mercredi 5 août 2020 - 03:44:52

Identifiants

Citation

Ngoc Tan Truong, Ali Khenchaf, Fabrice Comblet, Pierre Franck, Jean-Marc Champeyroux, et al.. GPS/GLONASS Data Fusion and Outlier Elimination to Improve the Position Accuracy of Receiver. 2019 IEEE Conference on Antenna Measurements Applications (CAMA), Oct 2019, Kuta, Indonesia. pp.191-194, ⟨10.1109/CAMA47423.2019.8959694⟩. ⟨hal-02457678⟩

Partager

Métriques

Consultations de la notice

65