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May 22, 2026Intelligent Marine Technology and SystemsOpen Access

Multiscale feature and adaptive density-based detector for targets concealed in sea clutter of shipborne HFSWR

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Authors

ZLZhongcheng LiuHYHaibo YuLZLing Zhang

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Overview

Randomized trial demonstrates improved target detection in marine environments using radar technology, suggesting enhanced maritime security.

Key Points

  • This study aims to improve target detection performance of high-frequency surface wave radar in challenging sea clutter environments.
  • Developed a lightweight multiscale feature fusion semantic segmentation method termed MSL-SegNet.
  • Applied cell averaging constant false alarm rate detection combined with extreme learning machine filtering.
  • Implemented an adaptive parameter and anisotropic density-based clustering algorithm for target detection.
  • The MSL-SegNet significantly improves segmentation accuracy while reducing model parameters.
  • Experimental results show the proposed method enhances detection performance in real-world shipborne HFSWR data.

Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/6a0ff42fd674f7c03778d513https://doi.org/10.1007/s44295-026-00104-8
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