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Remote Sensing Letters Volume 13, 2022 - Issue 11
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Research Article

Sea-surface small target detection using entropy features with dual-domain clutter suppression

Sainan Shia School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China;b Department of Signal Processing, Nanjing Xinda Institute of Safety and Emergency Management, Nanjing, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-7163-3716View further author information
ORCID Icon,
Li Jianga School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, ChinaView further author information
,
Ding Caoc Department of Signal and Information System, Nanjing Marine Radar Institute, Nanjing, ChinaView further author information
&
Yutao Zhangc Department of Signal and Information System, Nanjing Marine Radar Institute, Nanjing, ChinaView further author information
Pages 1142-1152 | Received 26 Oct 2021, Accepted 12 Sep 2022, Published online: 10 Oct 2022

Figures & data

Figure 1. Demonstration of the difference between sea clutter and returns with target in different domains. (a) Sea clutter in time domain. (b) Returns with target in time domain. (c) Sea clutter in Doppler domain. (d) Returns with target in Doppler domain. (e) Sea clutter in WDS. (f) Returns with target in WDS.

Figure 1. Demonstration of the difference between sea clutter and returns with target in different domains. (a) Sea clutter in time domain. (b) Returns with target in time domain. (c) Sea clutter in Doppler domain. (d) Returns with target in Doppler domain. (e) Sea clutter in WDS. (f) Returns with target in WDS.

Figure 2. Histogram distributions of DE and DRE. (a) DE and (b) DRE.

Figure 2. Histogram distributions of DE and DRE. (a) DE and (b) DRE.

Figure 3. Flowchart of FD-DRE detector.

Figure 3. Flowchart of FD-DRE detector.

Table 1. Description of IPIX datasets.

Figure 4. Influence of parameters on detection performance. (a) m = 2 and (b) c = 3.

Figure 4. Influence of parameters on detection performance. (a) m = 2 and (b) c = 3.

Figure 5. Detection results in the 15 datasets under four polarizations (N = 512, Pfa = 10−3). (a) HH. (b) HV. (c) VH. (d) VV.

Figure 5. Detection results in the 15 datasets under four polarizations (N = 512, Pfa = 10−3). (a) HH. (b) HV. (c) VH. (d) VV.

Table 2. Average detection probability at different observation time.

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