GPS/GLONASS Data Fusion and Outlier Elimination to Improve the Position Accuracy of Receiver - Archive ouverte HAL
Communication Dans Un Congrès Année : 2019

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

Résumé

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.
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Dates et versions

hal-02457678 , version 1 (28-01-2020)

Identifiants

Citer

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⟩
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