DocumentCode :
1036093
Title :
Coherent detection of radar targets in a non-gaussian background
Author :
Sangston, Kevin J. ; Gerlach, Kari R.
Author_Institution :
Naval Res. Lab., Washington, DC, USA
Volume :
30
Issue :
2
fYear :
1994
fDate :
4/1/1994 12:00:00 AM
Firstpage :
330
Lastpage :
340
Abstract :
The problem of detecting radar targets against a background of coherent, correlated, non-Gaussian clutter is studied with a two-step procedure. In the first step, the structure of the amplitude and the multivariate probability density functions (pdfs) describing the statistical properties of the clutter is derived. The starting point for this derivation is the basic scattering problem, and the statistics are obtained from an extension of the central limit theorem (CLT). This extension leads to modeling the clutter amplitude statistics by a mixture of Rayleigh distributions. The end product of the first step is a multidimensional pdf in the form of a Gaussian mixture, which is then used in step 2. The aim of step 2 is to derive both the optimal and a suboptimal detection structure for detecting radar targets in this type of clutter. Some performance results for the new detection processor are also given
Keywords :
probability; radar clutter; radar cross-sections; radar theory; signal detection; statistical analysis; Gaussian mixture; Rayleigh distributions; amplitude; central limit theorem; clutter amplitude statistics; coherent detection; multidimensional statistics; multivariate probability density functions; nonGaussian background; optimal detection structure; radar clutter; radar targets; statistical properties; suboptimal detection structure; two-step procedure; Background noise; Detectors; Gaussian noise; Matched filters; Meteorological radar; Radar clutter; Radar detection; Radar scattering; Statistical distributions; Statistics;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/7.272258
Filename :
272258
Link To Document :
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