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

Xianxiang Qin, Shilin Zhou, Huanxin Zou, Gui Gao

IEEE Geoscience and Remote Sensing Letters · 2012 · 185 citations · 17 references

Concepts

Abstract

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, <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</sub> , and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> 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.

References

17