Analysis and Possible Mitigation of Interferences Between Present and Next-Generation Marine Radars

被引:0
|
作者
Galati, Gaspare [1 ]
Pavan, Gabriele [1 ]
De Palo, Francesco [1 ]
机构
[1] Univ Roma Tor Vergata, Dept Elect Engn, Via Politecn 1, I-00133 Rome, Italy
关键词
Vessel traffic model; Radar visibility; Statistical analysis; Sea traffic model;
D O I
10.1007/978-3-319-63712-9_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The maritime traffic is significantly increasing in the recent decades due to its advantageous features related to costs, delivery rate and environmental compatibility. For this reasons it requires a high degree of control and an adequate assistance to the navigation. The related systems are the Vessel Traffic System (VTS), mainly using radar and the Automatic Identification System (AIS). In the recent years a new generation of marine radars with a lower cost of maintenance is being developed. They are based on the solid-state transmitter technology and uses coded "long pulse" in transmission, i.e. high "duty-cycle", with "pulse compression" in reception. The main drawbacks of these apparatuses are the interference effects that they might cause on existing marine radars, becoming critical when the traffic density increases. The AIS data (identity, location, intention and so on) can be useful to estimate the mutual distances among ships and the mean number of surroundings vessels, that is the number of marine radars in visibility. Using suitable models it is shown that the high duty-cycle of solid-state marine radars can generate severe interference to all marine radar sets in visibility with a significant reduction, well below the international regulations, of their detection capability. The mitigation of these damaging effects, not an easy task, can be achieved by changing the radar waveforms, i.e. resorting to Noise Radar Technology.
引用
收藏
页码:296 / 322
页数:27
相关论文
共 50 条
  • [31] Next-generation analysis of synovial tissue architecture
    Veale, Douglas J.
    Fearon, Ursula
    NATURE REVIEWS RHEUMATOLOGY, 2020, 16 (02) : 67 - 68
  • [32] Pathway analysis with next-generation sequencing data
    Jinying Zhao
    Yun Zhu
    Eric Boerwinkle
    Momiao Xiong
    European Journal of Human Genetics, 2015, 23 : 507 - 515
  • [33] Applications and data analysis of next-generation sequencing
    Vogl, Ina
    Benet-Pages, Anna
    Eck, Sebastian H.
    Kuhn, Marius
    Vosberg, Sebastian
    Greif, Philipp A.
    Metzeler, Klaus H.
    Biskup, Saskia
    Mueller-Reible, Clemens
    Klein, Hanns-Georg
    LABORATORIUMSMEDIZIN-JOURNAL OF LABORATORY MEDICINE, 2013, 37 (06): : 305 - 315
  • [34] Transcriptome analysis using next-generation sequencing
    Mutz, Kai-Oliver
    Heilkenbrinker, Alexandra
    Loenne, Maren
    Walter, Johanna-Gabriela
    Stahl, Frank
    CURRENT OPINION IN BIOTECHNOLOGY, 2013, 24 (01) : 22 - 30
  • [35] Next-generation analysis of synovial tissue architecture
    Douglas J. Veale
    Ursula Fearon
    Nature Reviews Rheumatology, 2020, 16 : 67 - 68
  • [36] Complexity Analysis of Next-Generation HEVC Decoder
    Viitanen, Marko
    Vanne, Jarno
    Hamalainen, Timo D.
    Gabbouj, Moncef
    Lainema, Jani
    2012 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 2012), 2012, : 882 - 885
  • [37] Next-generation sequencing for cancer drug development: the present and visions for the future
    Kahn, Scott M.
    PERSONALIZED MEDICINE, 2014, 11 (02) : 139 - 142
  • [38] Next-generation protein analysis in the pathology department
    Ahmed, Melek
    Broeckx, Glenn
    Baggerman, Geert
    Schildermans, Karin
    Pauwels, Patrick
    Van Craenenbroeck, Amaryllis H.
    Dendooven, Amelie
    JOURNAL OF CLINICAL PATHOLOGY, 2020, 73 (01) : 1 - 6
  • [39] DNA Next-Generation Sequencing (NGS): Present and Future in Clinical Practice
    Rubio, Santiago
    Adrian Pacheco-Orozco, Rafael
    Milena Gomez, Ana
    Perdomo, Sandra
    Garcia-Robles, Reggie
    UNIVERSITAS MEDICA, 2020, 61 (02):
  • [40] Pathway analysis with next-generation sequencing data
    Zhao, Jinying
    Zhu, Yun
    Boerwinkle, Eric
    Xiong, Momiao
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2015, 23 (04) : 507 - 515