Maximum likelihood estimation for compound-Gaussian clutter with inverse gamma texture

被引:194
作者
Balleri, Allessio
Nehorai, Arye
Wang, Jian
机构
[1] Univ Pisa, Dept Ingn Elect & Informat, I-56122 Pisa, Italy
[2] Univ Illinois, Dept Elect & Comp Engn, Chicago, IL 60607 USA
关键词
16;
D O I
10.1109/TAES.2007.4285370
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The inverse gamma distributed texture is important for modeling compound-Gaussian clutter (e.g. for sea reflections), due to the simplicity of estimating its parameters. We develop maximum-likelihood (ML) and method of fractional moments (MoFM) estimates to find the parameters of this distribution. We compute the Cramer-Rao bounds (CRBs) on the estimate variances and present numerical examples. We also show examples demonstrating the applicability of our methods to real lake-clutter data. Our results illustrate that, as expected, the ML estimates are asymptotically efficient, and also that the real lake-clutter data can be very well modeled by the inverse gamma distributed texture compound-Gaussian model.
引用
收藏
页码:775 / 780
页数:6
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