Coherent Detection Based on Texture Structure in Compound-Gaussian Clutter

SHI Sainan; SHUI Penglang; LIU Ming

doi:10.11999/JEIT151194

Volume 38 Issue 8

Sep. 2016

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SHI Sainan, SHUI Penglang, LIU Ming. Coherent Detection Based on Texture Structure in Compound-Gaussian Clutter[J]. Journal of Electronics & Information Technology, 2016, 38(8): 1969-1976. doi: 10.11999/JEIT151194

Citation:

SHI Sainan, SHUI Penglang, LIU Ming. Coherent Detection Based on Texture Structure in Compound-Gaussian Clutter[J]. Journal of Electronics & Information Technology, 2016, 38(8): 1969-1976. doi: 10.11999/JEIT151194

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Coherent Detection Based on Texture Structure in Compound-Gaussian Clutter

doi: 10.11999/JEIT151194

Funds:

The National Natural Science Foundation of China (61201296)

Received Date: 2015-10-29
Rev Recd Date: 2016-02-17
Publish Date: 2016-08-19

Abstract

Abstract

Traditional adaptive detectors are mostly derived under the assumption of independent and identically distributed texture. However, the texture correlation along the range cell exists in real sea clutter datasets. A new coherent detector based on texture structure is proposed by adding the information of texture correlation into the likelihood ratio test. Based on the prior knowledge that the texture correlation along range is generated by the swell modulation, the number of range cells related to the texture of the Cell Under Test (CUT) is determined, and this number provides the information for the texture of CUT. Experimental results using real datasets show that the proposed detector has better performance in comparison with the optimal detector in compound-Gaussian clutter with inverse gamma texture.
- Sea clutter,
- Compound-Gaussian model,
- Texture correlation,
- Adaptive detection

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References(21)

References

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