Persymmetric Adaptive Detection for Dual-Polarimetric Radar in Lognormal Texture Sea Clutter

This letter deals with the target detection problem for polarimetric marine radar. The sea clutter is modeled as the compound Gaussian (CG) distribution with lognormal texture. We propose three detectors based on the two-step generalized likelihood ratio test (GLRT), the complex value Rao, and Wald...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2024, Vol.21, p.1-5
Main Authors: Guo, Hongzhi, Wang, Zhihang, Wu, Haoqi, He, Zishu, Cheng, Ziyang
Format: Article
Language:English
Subjects:
Clutter
Competitors
Compound Gaussian (CG) clutter
Constant false alarm rate
constant false alarm rate (CFAR)
Covariance matrix
Detectors
Likelihood ratio
lognormal texture
Normal distribution
Polarimetric radar
Polarimetry
polarization detection
Radar
Radar clutter
Radar detection
Radar polarimetry
Spaceborne radar
Speckle
Surface clutter
Target detection
Texture
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Description
Summary:This letter deals with the target detection problem for polarimetric marine radar. The sea clutter is modeled as the compound Gaussian (CG) distribution with lognormal texture. We propose three detectors based on the two-step generalized likelihood ratio test (GLRT), the complex value Rao, and Wald tests by utilizing the persymmetric properties of the polarimetric speckle covariance matrix (CM). The lognormal texture component and the speckle CM are estimated by the maximum a posteriori (MAP) criterion and the polarimetric persymmetric fixed-point estimator, respectively. In addition, we provide proof of the constant false alarm rate (CFAR) properties of the designed polarimetric detectors. Moreover, we evaluate the detection performance of the proposed detectors in the simulated data and the measured sea clutter data, and the simulation results show the proposed detector outperforms the competitors by more than 1 dB in different situations.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2024.3407141