Automatic CFAR Ship Detection in Synthetic Aperture Radar Imagery
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In this research, we address the problem of automatic ship detection acquires from SAR (Synthetic Aperture Radar) images in complex marine environments. Assuming a non-Gaussian sea clutter with no prior knowledge about the presence or not of any clutter edge and/or interfering targets in the sliding reference window, we propose and analyze the detection performances of three CFAR (Constant False Alarm Rate) detectors in homogeneous and heterogeneous Log-normal or Weibull sea clutter.
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In this research, we address the problem of automatic ship detection acquires from SAR (Synthetic Aperture Radar) images in complex marine environments. Assuming a non-Gaussian sea clutter with no prior knowledge about the presence or not of any clutter edge and/or interfering targets in the sliding reference window, we propose and analyze the detection performances of three CFAR (Constant False Alarm Rate) detectors in homogeneous and heterogeneous Log-normal or Weibull sea clutter.
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In this research, we address the problem of automatic ship detection acquires from SAR (Synthetic Aperture Radar) images in complex marine environments. Assuming a non-Gaussian sea clutter with no prior knowledge about the presence or not of any clutter edge and/or interfering targets in the sliding reference window, we propose and analyze the detection performances of three CFAR (Constant False Alarm Rate) detectors in homogeneous and heterogeneous Log-normal or Weibull sea clutter.
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