Volume 9 Issue 2
May  2020
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Article Navigation >  Journal of Radars  > 2020  >  9(2): 335-342
HUANG Yinli, SUN Lu, GUO Liang, et al. Ship detection algorithm based on spatially variant apodization sidelobe suppression and order statistic-constant false alarm rate[J]. Journal of Radars, 2020, 9(2): 335–342. doi: 10.12000/JR19082
Citation: HUANG Yinli, SUN Lu, GUO Liang, et al. Ship detection algorithm based on spatially variant apodization sidelobe suppression and order statistic-constant false alarm rate[J]. Journal of Radars, 2020, 9(2): 335–342. doi: 10.12000/JR19082
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Ship Detection Algorithm Based on Spatially Variant Apodization Sidelobe Suppression and Order Statistic-Constant False Alarm Rate

doi: 10.12000/JR19082
  • 1.

    School of Physics and Optoelectronic Engineering, Xidian University, Xi’an 710071, China

  • 2.

    93128 troops of the Chinese people’s Liberation Army, Beijing 100085, China

  • 3.

    National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

  • 4.

    College of Geomatics, Xi’an University of Science and Technology, Xi’an 710000, China

  • 5.

    State Key Laboratory of Pulsed Power Laser Technology, National University of Defense Technology, Hefei 230037, China

Funds:  The National Natural Science Foundation of China (61001210), The National Key R&D Program of China (2017YFC1405600), The Natural Science Fundamental of Shaanxi Province (2017JQ6021), The Fundamental Research Funds for the Central Universities (JB180213), Open Research Fund of State Key Laboratory of Pulsed Power Laser Technology (SKL2018KF06), The Research Plan Project of National University of Defense Technology (ZK180102)
More Information
  • Corresponding author: GUO Liang, lguo@mail.xidian.edu.cn
  • Received Date: 2019-09-10
  • Rev Recd Date: 2019-12-09
    • Available Online: 2019-12-30
  • Publish Date: 2020-04-01
    Abstract
  • The special imaging mechanism of the Synthetic Aperture Radar (SAR) causes the sidelobe effect on SAR images. In target detection, the sidelobe effect changes the shapes of strong reflective targets, which results in the problems of localization difficulty and localization error. To solve this problem, this paper proposes a ship detection algorithm based on Spatially Variant Apodization (SVA) and Order Statistic-Constant False Alarm Rate (OS-CFAR). First, the global-CFAR algorithm is used to prescreen the potential target points, which reduces the computational burden of the following steps. Second, the SVA algorithm is modified to improve the speed of sidelobe suppression and applied to the raw complex image data. Then, the nonlinear method OS-CFAR is used to detect the targets on the processed image, and the morphological dilation processing is used to make up for the wrong suppressed points caused by the SVA algorithm. Finally, the GF-3 SAR images are used to test the algorithm and the comparison of the image contrast and detected numbers in the results with SVA and without SVA verifies the effectiveness of the proposed algorithm.

     

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