GENERALIZED LIKELIHOOD RATIO TEST FOR FINITE MIXTURE MODEL OF K-DISTRIBUTED RANDOM VARIABLES

被引：0

作者：

Tucker, J. Derek ^{[1
]}

Cobb, J. Tory ^{[1
]}

Azimi-Sadjadi, Mahmood R. ^{[2
]}

机构：

[1] USN, Ctr Surface Warfare, Panama City Div, Panama City, FL 32407 USA

[2] Colorado State Univ, Dept Elect & Comp Engn, Ft Collins, CO 80523 USA

来源：

2011 IEEE DIGITAL SIGNAL PROCESSING WORKSHOP AND IEEE SIGNAL PROCESSING EDUCATION WORKSHOP (DSP/SPE) | 2011年

关键词：

Binary hypothesis testing; K-distributed clutter; non-Gaussian signal detection; sonar imagery; underwater target detection;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper a new detection method for sonar imagery is developed for K-distributed background clutter using a finite mixture model (FMM) of K-distributions. The method for estimation of the parameters of the FMM and a generalized log-likelihood ratio test is derived. The detector is compared to the corresponding counterparts derived for the standard K-, Gaussian, and Rayleigh distributions. Test results of the proposed method on a data set of synthetic aperture sonar (SAS) images is also presented. This database contains images with synthetically generated targets of different shapes inserted into real SAS background imagery. Results illustrating the effectiveness of the FMM K-distributed detector are presented in terms of probability of detection, false alarm rates, and receiver operating characteristic (ROC) curves for various bottom clutter conditions.

引用

页码：443 / 448

页数：6

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