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"Exploring the Potential of the Deep-Learning-Aided Kalman Filter for ..."

Shuo Li et al. (2024)

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DOI: 10.1109/TAES.2023.3325791

access: closed

type: Journal Article

metadata version: 2024-07-04

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  - https://dblp.org/rec/journals/taes/LiMPM24
Shuo Li, Maxim Mikhaylov, Thomas Pany, Nikolay Mikhaylov:
Exploring the Potential of the Deep-Learning-Aided Kalman Filter for GNSS/INS Integration: A Study on 2-D Simulation Datasets. IEEE Trans. Aerosp. Electron. Syst. 60(3): 2683-2691 (2024)

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