• DocumentCode
    3087391
  • Title

    An association algorithm of ship-group targets based on topological and attributive characteristics

  • Author

    Chunyan Lu ; Huanxin Zou ; Shilin Zhou ; Hao Sun

  • Author_Institution
    Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2012
  • fDate
    16-18 Dec. 2012
  • Firstpage
    34
  • Lastpage
    38
  • Abstract
    When the sensors´ orientating precision and their identification performance are poor, it is difficult to get effective group members association by their position or attributive characteristics. This paper presents a novel algorithm for ship-group targets association of spaceborne electronic reconnaissance data and optical imaging data. The contributions of the paper are: (1) Firstly, a new shape descriptor, named Point Pair Topological Characteristics (PPTC), is proposed to describe the topological characteristics of a ship-group. (2) Secondly, based on the PPTC descriptor, we present a basic probability assignment function, which is used to evaluate the comparability between PPTC. (3) Thirdly, we combine both PPTC and attributive characteristics together to construct the initial association probability matrix. Thus, the independent topological and attributive information are integrated to a synthetic association measurement. Experimental results on both synthetic and real word data demonstrate the effectiveness and robustness of our method.
  • Keywords
    matrix algebra; probability; sensor fusion; ships; space vehicles; PPTC; association probability matrix; attributive characteristics; group member association; optical imaging data; point pair topological characteristics; sensor orientating precision; shape descriptor; ship-group target association algorithm; ship-group topological characteristics; spaceborne electronic reconnaissance data; synthetic association measurement; Marine vehicles; TV; association; optical imaging reconnaissance; ship-group targets; spaceborne electronic reconnaissance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4673-1272-1
  • Type

    conf

  • DOI
    10.1109/CVRS.2012.6421229
  • Filename
    6421229