Acta Photonica Sinica, Volume. 51, Issue 2, 0210008(2022)

Lightweight Synthetic Aperture Radar Ship Detection Algorithm with Enhanced Receptive Field

Yanni WANG, Xuesong SUN*, and Lixian YU
Author Affiliations
  • School of Information and Control Engineering,Xi′an University of Architecture and Technology,Xi′an710055,China
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    Figures & Tables(19)
    The proposed network structure
    The operation process of channel shuffle
    Building blocks of ShuffleNetV2
    Spatial Attention Module
    SAM heatmap
    The structure of SSPP
    Feature map of SSPP
    PANet structure
    Improved PANet structure
    Sample images and labels in SSDD
    Mosaic data enhancement
    Target detection results of the improved algorithm in different scenarios
    P-R curve(the threshold changed from 0.05 to 0.95)
    Comparison of detection algorithms for complex background of near-shore ships
    Comparison of detection algorithms for small target ships in the open sea
    • Table 1. Overall architecture of ShuffleNetV2

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      Table 1. Overall architecture of ShuffleNetV2

      LayerKernel sizeStrideRepeatOutput sizeOutput channels(1×)
      Image---224×2243

      Conv1

      MaxPool

      3×3

      3×3

      2

      2

      1

      1

      112×112

      56×56

      24

      24

      Stage2

      -

      -

      2

      1

      1

      3

      28×28

      28×28

      116
      Stage3

      -

      -

      2

      1

      1

      7

      14×14

      14×14

      232
      Stage4

      -

      -

      2

      1

      1

      3

      7×7

      7×7

      464
      Conv51×1117×71 024
      GlobalPool7×7--7×7-
      FC----1 000
      FLOPs----146 M
      Weights----2.3 M
    • Table 2. Accuracy comparison results of different modules

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      Table 2. Accuracy comparison results of different modules

      SSPPSAMPANmAP/%Speed/FPS
      ×××85.652
      ××90.250
      ×91.548
      ×93.447
      94.746
    • Table 3. Comparison of different detection algorithms in near shore and open sea scenes

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      Table 3. Comparison of different detection algorithms in near shore and open sea scenes

      AlgorithmSSDYOLOv3YOLOv4YOLOv3-tinyYOLOv4-tinyOurs
      Near shorePrecision/%74.275.378.469.372.380.6
      Recall/%91.692.491.578.583.894.3
      Open seaPrecision/%87.392.396.787.591.297.8
      Recall/%93.495.498.283.485.697.2
    • Table 4. Performance comparison of different detection algorithms

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      Table 4. Performance comparison of different detection algorithms

      AlgorithmBackboneFLOPsParamsSpeed/FPSModel size/MBmAP/%
      SSDVGG16130.9 B99.6 M2810089.3
      YOLOv3Darknet53156.3 B246.1 M2623692.3
      YOLOv4CSPDarknet53128.5 B255.7 M2724495.6
      YOLOv3-tinyDarknet53_tiny5.62 B8.86 M3533.490.3
      YOLOv4-tinyCSPdarknet53_tiny6.96 B6.06 M3822.693.8
      OursShuffleNetV21.52 B2.34 M465.394.7
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    Yanni WANG, Xuesong SUN, Lixian YU. Lightweight Synthetic Aperture Radar Ship Detection Algorithm with Enhanced Receptive Field[J]. Acta Photonica Sinica, 2022, 51(2): 0210008

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    Paper Information

    Category:

    Received: Jul. 27, 2021

    Accepted: Sep. 3, 2021

    Published Online: May. 19, 2022

    The Author Email: SUN Xuesong (sxs2049@163.com)

    DOI:10.3788/gzxb20225102.0210008

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