To monitor the sea-state and detect low-speed targets beyond the line-of-sight limitation, high-frequency (HF) sky-wave radar needs to extract the sea-clutter Doppler spectrum and suppress radio-frequency interference (RFI). However, this is hard for traditional radar processing techniques in practice. Instead, this study proposes to tackle these problems based on image recognition methods. By converting the range-Doppler (RD) map into a grey image, the extraction of sea-clutter and RFI regions becomes two problems of image segmentation. The sea-clutter region is extracted by the distance regularised level set evolution algorithm, based on a binary image which uses threshold segmentation to roughly classify sea-clutter pixels and noise pixels. To extract the RFI region, the authors develop a straight line detection algorithm which employs the LOG operator to mitigate the sea-clutter and highlight the RFI lines. Simulation results demonstrate that the proposed approaches are effective in the RD map with undesired RFI lines near the sea-clutter.

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Extraction of sea-clutter and RFI regions based on image segmentation for high-frequency sky-wave radar

References

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