Anomaly Location and Recovery for SINS/DVL/PS Integrated Navigation System via Transfer Learning-Based Dual-LSTM Network-Reference-Cited by-同舟云学术

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Anomaly Location and Recovery for SINS/DVL/PS Integrated Navigation System via Transfer Learning-Based Dual-LSTM Network

Published:2024-04-01 Issue:7 Volume:24 Page:11783-11795
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Zhao Yuxin¹^ORCID,Chen Yang¹^ORCID,Chen Liheng²^ORCID,Ben Yueyang¹^ORCID,Yao Weiran³^ORCID

Affiliation:

1. College of Intelligent Systems Science and Engineering and the Engineering Research Center of Navigation Instruments, Ministry of Education, Harbin Engineering University, Harbin, China

2. Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macau, China

3. School of Astronautics, Harbin Institute of Technology, Harbin, China

Funder

National Natural Science Foundation of China

Macao Young Scholars Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10487994/10436579.pdf?arnumber=10436579

Reference41 articles.

1. Surface path tracking method of autonomous surface underwater vehicle based on deep reinforcement learning

2. Autonomous Underwater Intervention: Experimental Results of the MARIS Project

3. GNSS/INS/OD/NHC Adaptive Integrated Navigation Method Considering the Vehicle Motion State

4. INS/DVL/PS Tightly Coupled Underwater Navigation Method With Limited DVL Measurements

5. A New Coupled Method of SINS/DVL Integrated Navigation Based on Improved Dual Adaptive Factors

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