Automatic CFAR Ship Detection in Synthetic Aperture Radar Imagery

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.

Autorentext

Hicham Madjidi was born in Djelfa, Algeria. He received a B.S. degree in Computer Science in 2013, an M.Sc. degree in Networking and Telecommunications in 2018, both from the University of Djelfa, and a Doctorate degree in Signals and Telecommunication Systems from the University of Constantine 1 in 2023. His current research interests include SAR.