• DocumentCode
    619714
  • Title

    The application of maximum differential algorithm in adaptive ocean sampling

  • Author

    Qingchun Li ; Junwei Gao ; Sheng Guan ; Bin Zhang ; Ziwen Leng

  • Author_Institution
    Coll. of Autom. Eng., Qingdao Univ., Qingdao, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    328
  • Lastpage
    332
  • Abstract
    This paper presents a technique for adaptive ocean sampling using ocean sampling platforms equipped with multiple sensors. The virtual environment of 2D ocean sampling is established, so as to simulate the ocean sampling region by means of the sampling platforms. There are three important phases which can be written as collecting scientific data, drawing the sampling area, and utilizing the maximum differential algorithm (MDA) in ocean sampling. By analyzing the sampling data and using the maximum differential algorithm, the sampling platforms achieve the optimizing sampling path. The simulation results by adaptive ocean sampling of single sampling platform and multiple platforms show that the proposed approach is effective and feasible. This method can be applied to conduct the moving direction based on the ocean sampling platforms.
  • Keywords
    autonomous underwater vehicles; oceanographic techniques; optimisation; sampling methods; sensor fusion; 2D ocean sampling; MDA; adaptive ocean sampling technique; maximum differential algorithm; multiple sensors; ocean sampling region simulation; sampling area; sampling data; sampling path optimization; scientific data collection; virtual environment; Adaptation models; Adaptive systems; Algorithm design and analysis; Oceans; Path planning; Sensors; Underwater vehicles; Adaptive sampling; Maximum differential algorithm; Ocean sampling platforms; Optimal sampling path;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6560943
  • Filename
    6560943