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Volume 43 Issue 11
Nov.  2021
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Yanling SHI, Tingting YAO, Yaxing GUO. Floating Small Target Detection Based on Graph Connected Density in Sea Surface[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3185-3192. doi: 10.11999/JEIT201028
Citation: Yanling SHI, Tingting YAO, Yaxing GUO. Floating Small Target Detection Based on Graph Connected Density in Sea Surface[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3185-3192. doi: 10.11999/JEIT201028

Floating Small Target Detection Based on Graph Connected Density in Sea Surface

doi: 10.11999/JEIT201028
  • Received Date: 2020-12-07
  • Rev Recd Date: 2021-03-21
  • Available Online: 2021-04-09
  • Publish Date: 2021-11-23
  • Due to the weak energy of the floating small targets, it is hard to be detected in sea surface. Relying on the energy, the traditional detectors based on statistical model inevitable loss the detection performance, regardless of the correlation between the frequency domain amplitudes. Therefore, in the paper, the correlation between the frequency domain amplitudes is considered by using the graph. Firstly, the connected density is calculated by the correlation between the frequency domain amplitudes of the echo pulses. Secondly, an adjacency matrix is generated based on the correlation. Thirdly, the adjacency matrix is converted to a Laplacian matrix. Lastly, the maximum eigenvalue of the Laplacian matrix is extracted as the detection feature. Thus, the detector based on the connected density of the graph is proposed for the floating small targets in sea surface. The analysis of the connected density of the measured Ice multiParameter Imaging X-band(IPIX) radar data shows that the graph composed by the sea clutter is relatively dense, whereas the graph composed by the floating small targets is relatively sparse. Thus, the connected density can effectively distinguish the floating small targets between the sea clutter. Furthermore, the experimental results show that, compared with other algorithms, the detection performance of the proposed connected density of the graph algorithm is obviously superior.
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