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Remote Sensing Monitoring Method Based on BDS-Based Maritime Joint Positioning Model

Xiang Wang1,2, Jingxian Liu1, Osamah Ibrahim Khalaf3,*, Zhao Liu1,*

1 Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan, 430063, China
2 Donghai Navigation Safety Administration, Ministry of Transport of the People’s Republic of China, Shanghai, 201206, China
3 Al-Nahrain Nanorenewable Energy Research Centre, Al-Nahrain University, Baghdad, Iraq

* Corresponding Authors: Osamah Ibrahim Khalaf. Email: ; Zhao Liu. Email:

(This article belongs to this Special Issue: Modeling and Analysis of Autonomous Intelligence)

Computer Modeling in Engineering & Sciences 2021, 127(2), 801-818. https://doi.org/10.32604/cmes.2021.013568

Abstract

Complicated sea conditions have a serious impact on ship navigation safety and even maritime accidents. Accordingly, this paper proposes a remote sensing monitoring method based on the Beidou Navigation Satellite System (BDS) maritime joint positioning model. This method is mainly based on the BDS and multiple Global Navigation Satellite Systems (GNSS) to build a data fusion model, which can capture more steady positioning, navigation, and timing (PNT) data. Compared with the current Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS) mandatory used by the International Maritime Organization (IMO), this model has the characteristics of more accurate positioning data and stronger stability. The static and dynamic measurement show that such a model works for maritime ships and maritime engineering. Combined with the Ship’s Automatic Identification System (AIS) and Geographic Information System (GIS), a BDS-based remote sensing monitoring method can cover the world, serve maritime ships and construct maritime engineering.

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Cite This Article

Wang, X., Liu, J., Khalaf, O. I., Liu, Z. (2021). Remote Sensing Monitoring Method Based on BDS-Based Maritime Joint Positioning Model. CMES-Computer Modeling in Engineering & Sciences, 127(2), 801–818.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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