• DocumentCode
    3713721
  • Title

    Synthetic SAR/IR database generation for sensor fusion-based A.T.R.

  • Author

    Jin-Ju Won;Sungho Kim;Youngrea Cho;Woo-Jin Song;So-Hyun Kim

  • Author_Institution
    Department of Electronic Engineering Yeungnam University, Gyeonsan, Korea
  • fYear
    2015
  • Firstpage
    421
  • Lastpage
    424
  • Abstract
    Recently, the sensor fusion research has been in progress for effective ground target detection. SAR and IR sensors are complementary because the IR sensor has a high resolution, SAR sensor is not effected by the weather. In research, The DB of the SAR/IR sensor is essential. But database(DB) of the SAR/IR sensor dose not exist or is not released. It is also difficult to acquire the DB directly because of cost and environmental issues. Therefore, this paper proposed a method to build the DB with synthetic image generation simulator OKTAL-SE. We generate day and night images, and compare the features.
  • Keywords
    "Atmospheric modeling","Robot sensing systems","Image generation","Meteorology","Computational modeling","Sensor fusion","Object detection"
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous Robots and Ambient Intelligence (URAI), 2015 12th International Conference on
  • Type

    conf

  • DOI
    10.1109/URAI.2015.7358893
  • Filename
    7358893