Electronics Optics & Control, Volume. 32, Issue 1, 74(2025)

A Ship Target Detection Algorithm for SAR Images

MENG Fanlong1...2, QI Xiangyang1 and FAN Huaitao1 |Show fewer author(s)
Author Affiliations
  • 1Institute of Aerospace Information Innovation, Chinese Academy of Sciences, Beijing 100000, China
  • 2School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100000, China
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    Ship target detection based on SAR images continues to face challenges due to environmental complexity, ship target dispersion, and scale diversity.This paper proposes a ship target detection algorithm specifically for SAR images.Firstly, a ship feature refinement module is developed based on deformable convolution to enhance the feature extraction capabilities for ship targets with significant aspect ratios. Secondly, a ship spatial pyramid aggregation structure is integrated at the end of the backbone network, thereby improving the global feature extraction capability for ship targets.Finally, a scale expansion feature pyramid network is designed to facilitate the interaction between shallow and deep feature information of the ship, thereby enhancing the detection capability for multiscale ship targets.Experimental results indicate that the proposed algorithm achieves a mean Average Precision (mAP) of 93.72% and an F1 score of 89.70% on the HRSID dataset, outperforming all the comparative methods and demonstrating effective detection performance.

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    MENG Fanlong, QI Xiangyang, FAN Huaitao. A Ship Target Detection Algorithm for SAR Images[J]. Electronics Optics & Control, 2025, 32(1): 74

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    Paper Information

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    Received: Jan. 5, 2024

    Accepted: Jan. 10, 2025

    Published Online: Jan. 10, 2025

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2025.01.012

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