This paper presents an approach to increase the knowledge gained during maritime surveillance using high-resolution ICEYE Synthetic Aperture Radar (SAR) imagery, by estimating the three-dimensional features of vessels. Specifically, the height and mass, alongside traditional two-dimensional length, and width parameters. By analysing the SAR shadow and overlay, we calculate the height of the deck and bridge on the vessel, leading to an estimation of its cargo weight. This enhances maritime surveillance by providing a deeper understanding of vessel characteristics critical for security applications. While we utilize Ultralytics’ YOLOv8 deep learning for initial ship detection, the primary focus is on the detailed estimation of 3D features, a capability not previously demonstrated with SAR imagery.
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Sørensen et al. (2024) studied this question.
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