NDLI: Generalized likelihood ratio test for finite mixture model of K-distributed random variables

Content Provider	IEEE Xplore Digital Library
Author	Tucker, J.D. Cobb, J.T. Azimi-Sadjadi, M.R.
Copyright Year	2011
Description	Author affiliation: Naval Surface Warfare Center, Panama City Division, Florida 32407-7001, USA (Tucker, J.D.; Cobb, J.T.) \|\| Colorado State University, Department of Electrical and Computer Engineering, Fort Collins, 80523-1373, USA (Azimi-Sadjadi, M.R.)
Abstract	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 theFMMK-distributed detector are presented in terms of probability of detection, false alarm rates, and receiver operating characteristic (ROC) curves for various bottom clutter conditions.
Starting Page	443
Ending Page	448
File Size	173918
Page Count	6
File Format	PDF
ISBN	9781612842264
e-ISBN	9781612842271
DOI	10.1109/DSP-SPE.2011.5739255
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-01-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors Sonar detection Thyristors Clutter Pixel Estimation underwater target detection Binary hypothesis testing K-distributed clutter non-Gaussian signal detection sonar imagery
Content Type	Text
Resource Type	Article

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