Neural Networks Aided Unscented Kalman Filter for Integrated INS/GNSS Systems-Reference-Cited by-同舟云学术

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Neural Networks Aided Unscented Kalman Filter for Integrated INS/GNSS Systems

Published:2020-05 Issue: Volume: Page:
ISSN:
Container-title:2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)
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Author:

Al Bitar N.,Gavrilov A.I.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9127408/9133728/09133878.pdf?arnumber=9133878

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Hybrid Algorithm of LSTM and Factor Graph for Improving Combined GNSS/INS Positioning Accuracy during GNSS Interruptions;Sensors;2024-08-29

2. Hybrid Multi-Sensor Navigation System With Uncertainty Correction for GNSS-Denied Environments;AIAA SCITECH 2024 Forum;2024-01-04

3. Integrating GRU with a Kalman Filter to Enhance Visual Inertial Odometry Performance in Complex Environments;Aerospace;2023-10-29

4. A GNSS Positioning Algorithm Assisted by LSTM Neural Network and EKF;2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops);2023-08-10

5. Designing INS/GNSS integrated navigation systems by using IPO algorithms;Neural Computing and Applications;2023-04-12

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