Maritime ship tracking is a crucial component of maritime surveillance, holding paramount importance in both military and civilian spheres. This study proposes a maritime ship tracking concept utilizing Synthetic Aperture Radar (SAR) constellations, along with a Detection-Matching-Tracking (DMT) implementation strategy. Specifically, we design a novel SAR ship detector capable of locating and segmenting all ships present within image sequences provided by an SAR constellation. Following ship detection, we employ an enhanced two-channel convolutional neural network (2-channel CNN) to perform ship matching between the target ship and potential candidates. Ultimately, based on the matching results, we can plot the space-time trajectory of the tracked ship. The preliminary experiment demonstrates that the proposed methodology is feasible and has the potential to track ships in open seas.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Maritime ship tracking based on SAR constellation: a preliminary implementation


    Contributors:
    Bruzzone, Lorenzo (editor) / Bovolo, Francesca (editor) / Lang, Haitao (author) / Niu, Lihui (author) / Li, Jialu (author) / Li, Wenjing (author) / Ma, Li (author)

    Conference:

    Image and Signal Processing for Remote Sensing XXIX ; 2023 ; Amsterdam, Netherlands


    Published in:

    Proc. SPIE ; 12733


    Publication date :

    2023-10-19





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    The GANDER constellation for maritime disaster mitigation

    Da Silva Curiel, R. A. / Jolly, G. / Zheng, Y. et al. | British Library Conference Proceedings | 1999


    The Gander Constellation for Maritime Disaster Mitigation

    Da Silva Curiel, R. A. / Jolly, G. / Zheng, Y. et al. | British Library Conference Proceedings | 1998


    Maritime Ship Tracking Algorithm Based on Improved YOLOv8 and StrongSORT

    Wu, Chen / Song, Yucun / Ge, Quanbo | IEEE | 2024


    Intelligent Ship Route Tracking Method Based on Practical Maritime Experience

    Liu, Xiao / Deng, Hua / Wu, Yong et al. | IEEE | 2024


    MARITIME FACTORY SHIP

    KRAVITZ ARNOLD | European Patent Office | 2025

    Free access