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YANG Huizhang, XI Feng, LIU Zhong, et al. Sub-band contrast and entropy of SAR images: Concepts and applications to interference detection and suppression[J]. Journal of Radars, in press. doi: 10.12000/JR25027
Citation: YANG Huizhang, XI Feng, LIU Zhong, et al. Sub-band contrast and entropy of SAR images: Concepts and applications to interference detection and suppression[J]. Journal of Radars, in press. doi: 10.12000/JR25027
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Sub-band Contrast and Entropy of SAR Images: Concepts and Applications to Interference Detection and Suppression

DOI: 10.12000/JR25027
  • 1.

    School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

  • 2.

    Nanjing Research Institute of Electronics Technology, Nanjing 210039, China

  • 3.

    Department of Electronic Engineering, Tsinghua University, Beijing 100084, China

Funds:  The National Natural Science Foundation of China (62301259, 62171224), The Fundamental Research Funds for the Central Universities (30924010914)
More Information
  • Corresponding author: YANG Huizhang, hzyang@njust.edu.cn
  • Received Date: 2025-02-12
  • Rev Recd Date: 2025-05-26
    • Available Online: 2025-06-05
    Abstract
  • Spaceborne Synthetic Aperture Radar (SAR) data may be prone to interrupted-sampling repeater jamming and many common unintentional interferences, such as linear frequency modulated pulses. In this paper, we first divide a single-look complex SAR image into multiple sub-band images of equal bandwidth in the range frequency domain. Then, we model the pixel intensity of these sub-band images and analyze the fluctuation mechanism of interfering and noninterfering pixels across the sub-bands. The findings reveal that the energy distribution of interfering pixels is uneven across different sub-bands, leading to substantial intensity fluctuations within the sub-band domain, whereas the intensity of noninterfering pixels remains relatively stable. Based on this observation, we define sub-band contrast and sub-band entropy as statistical measures to quantify fluctuation characteristics across the sub-bands. These measures are then compared with certain thresholds to obtain detection results. Statistical analysis revealed that under noninterfering conditions, these two statistics approximately follow the beta distribution. By leveraging this finding, we fit the distributions of these measures using the beta distribution and develop a method to determine detection thresholds under the constant-false-alarm-rate criterion. Experimental results showed that the proposed method can effectively detect interrupted-sampling repeater jamming and common unintentional interferences. In addition, we investigated the impact of the jamming-to-signal ratio on detection performance and verified the reliability and stability of the method via Monte Carlo simulations. Furthermore, we introduced an interference suppression technique based on a rank-1 model to reduce the adverse effects of interference on downstream tasks. This technique is capable of adaptively suppressing interference in detected regions.

     

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