A CFAR Detection Algorithm for Generalized Gamma Distributed Background in High-Resolution SAR Images

In this letter, a novel constant false alarm rate (CFAR) detection algorithm for high-resolution synthetic aperture radar (SAR) images is proposed with the generalized gamma distribution (GΓD) modeling the background. At first, the method of log-cumulants is introduced for estimating the parameters...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2013-07, Vol.10 (4), p.806-810
Main Authors: Qin, Xianxiang, Zhou, Shilin, Zou, Huanxin, Gao, Gui
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Clutter
Constant false alarm rate (CFAR)
Distributed algorithms
Estimation
Exact solutions
Gamma function
generalized gamma distribution (G Gamma D)
Image resolution
Inverse
Mathematical analysis
method of log-cumulants (MoLC)
Object detection
Remote sensing
Synthetic aperture radar
synthetic aperture radar (SAR)
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Summary:In this letter, a novel constant false alarm rate (CFAR) detection algorithm for high-resolution synthetic aperture radar (SAR) images is proposed with the generalized gamma distribution (GΓD) modeling the background. At first, the method of log-cumulants is introduced for estimating the parameters of the GΓD. In addition, a closed-form expression for the detection threshold of the CFAR algorithm is derived, which refers to the inverse incomplete gamma function. Finally, comparing with the algorithms using the Weibull, K A , and G A 0 distributions for background, the advantages of the proposed algorithm, including maintaining the false alarm rate and the efficiency, are validated with an actual high-resolution SAR image.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2012.2224317