Enhancing train position perception through AI-driven multi-source information fusion

DOI10.1007/S11768-023-00158-7zbMath1530.93211OpenAlexW4386377776MaRDI QIDQ6061932

Haifeng Song, Hai-Rong Dong, Zheyu Sun, Hongwei Wang, Zixuan Zhang, Tianwei Qu

Publication date: 30 November 2023

Published in: Control Theory and Technology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11768-023-00158-7

zbMATH Keywords

deep learningtrain positioningmulti-source information fusiondynamic adaptive model

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Filtering in stochastic control theory (93E11) Adaptive control/observation systems (93C40)

Cites Work

• Adaptive Kalman filter for MEMS IMU data fusion using enhanced covariance scaling
• A Novel Adaptive Kalman Filter With Inaccurate Process and Measurement Noise Covariance Matrices
• The Invariant Extended Kalman Filter as a Stable Observer

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