Sea Clutter Image Segmentation Method of High Frequency Surface Wave Radar Based on the Improved Deeplab Network

DOI Web Site 参考文献11件
  • CHEN Haotian
    College of Information and Engineering, Hebei GEO University Department of Software Convergence Engineering, Kunsan National University
  • LEE Sukhoon
    Department of Software Convergence Engineering, Kunsan National University
  • YAO Di
    Department of Electronic and Information Engineering, Harbin Institute of Technology
  • JEONG Dongwon
    Department of Software Convergence Engineering, Kunsan National University

抄録

<p>High Frequency Surface Wave Radar (HFSWR) can achieve over-the-horizon detection, which can effectively detect and track the ships and ultra-low altitude aircrafts, as well as the acquisition of sea state information such as icebergs and ocean currents and so on. However, HFSWR is seriously affected by the clutters, especially sea clutter and ionospheric clutter. In this paper, we propose a deep learning image semantic segmentation method based on optimized Deeplabv3+ network to achieve the automatic detection of sea clutter and ionospheric clutter using the measured R-D spectrum images of HFSWR during the typhoon as experimental data, which avoids the disadvantage of traditional detection methods that require a large amount of a priori knowledge and provides a basis for subsequent the clutter suppression or the clutter characteristics research.</p>

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