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    Tytuł:
    Research on radiation characteristics of plasma Yagi antenna based on AIS base station in ships’ routeing waters
    Autorzy:
    Sun, Y.
    Chen, Y.
    Kong, F.
    Wei, Y.
    Zhan, F.
    Zhao, J. S.
    Powiązania:
    https://bibliotekanauki.pl/articles/117021.pdf
    Data publikacji:
    2020
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    radio navigation
    radiation characteristics
    plasma Yagi antenna
    ships routeing
    AIS base station
    AIS based shipping routes
    ships routeing waters
    Automatic Identification System (AIS)
    Opis:
    A Yagi plasma antenna model was established by HFSS according to the relationship between plasma dielectric constant and electron density. The patterns were simulated by changing plasma parameters and the number of director dipoles. Results show that when the passive vibrators were switched off, the antenna is omnidirectional antenna. The directionality increases with the increase of the number of passive dipole and the main lobe of which narrows down. Then the plasma Yagi antenna model is established by plasma tube, the gain changed by changing the number of passive dipoles, so the plasma Yagi antenna has a very good reconfigurability. Results prove that the feasibility of the plasma Yagi antenna can be used on AIS base station of Ships’ Routeing waters. It can promote the communication and capability of maritime supervision in Ships’ Routeing waters.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2020, 14, 1; 179-184
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Ship recognition and tracking system for intelligent ship based on deep learning framework
    Autorzy:
    Liu, B.
    Wang, S. Z.
    Xie, Z. X.
    Zhao, J. S.
    Li, M. F.
    Powiązania:
    https://bibliotekanauki.pl/articles/117419.pdf
    Data publikacji:
    2019
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    intelligent ship
    deep learning framework
    ship recognition system
    ship tracking system
    ship recognition and tracking system
    intelligent navigation
    autonomous ship
    maritime safety
    Opis:
    Automatically recognizing and tracking dynamic targets on the sea is an important task for intelligent navigation, which is the prerequisite and foundation of the realization of autonomous ships. Nowadays, the radar is a typical perception system which is used to detect targets, but the radar echo cannot depict the target’s shape and appearance, which affects the decision-making ability of the ship collision avoidance. Therefore, visual perception system based on camera video is very useful for further supporting the autonomous ship navigational system. However, ship’s recognition and tracking has been a challenge task in the navigational application field due to the long distance detection and the ship itself motion. An effective and stable approach is required to resolve this problem. In this paper, a novel ship recognition and tracking system is proposed by using the deep learning framework. In this framework, the deep residual network and cross-layer jump connection policy are employed to extract the advanced ship features which help enhance the classification accuracy, thus improves the performance of the object recognition. Experimentally, the superiority of the proposed ship recognition and tracking system was confirmed by comparing it with state of-the-art algorithms on a large number of ship video datasets.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2019, 13, 4; 699-705
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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