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Please use this identifier to cite or link to this item: http://hdl.handle.net/1947/10168

Title: Nonhomogeneity Detection in CFAR Reference Windows Using the Mean-to-Mean Ratio Test.
Report number: DSTO-TR-2608
AR number: AR-015-113
Classification: Unclassified
Report type: Technical Report
Authors: Cao, T.V.
Issue Date: 2011-11
Division: Electronic Warfare & Radar Division
Abbreviation: EWRD
Release authority: Chief, Electronic Warfare & Radar Division
Task sponsor: CDS
Task number: DST 07/213
File number: 2011/1196856/1
Pages or format: 16
References: 21
DSTORL/DEFTEST terms: Radar detection
Constant false alarm rate
Radar clutter
Abstract: A new method designated as the mean-to-mean ratio (MMR) test is proposed for the detection of nonhomogeneities in a radar's Constant False Alarm Rate (CFAR) reference window. No a priori knowledge of the nonhomogeneity topology is assumed. Analysis using the Monte-Carlo method based on Rayleigh clutter and Swerling I target models is presented. Target-like interferences which seriously degrade the detection performance of the cell-averaging CFAR detector can be detected with a higher probability by the MMR test.
Executive summary: In radar Constant False Alarm Rate (CFAR) signal processing, the cell-averaging CFAR (CA-CFAR) is the most popular algorithm employed in practical radar detection. As the CA-CFAR detection performance degrades seriously when the reference window used in the estimation of the mean noise level is contaminated by nonhomogeneous samples, many modifications have been proposed. Each of these modified CFAR algorithms has its own advantages and drawbacks, depending on the topology of the nonhomogeneity. They all, nevertheless, share the same design methodology in that an attempt is made to censor out the inappropriate reference samples. Since censoring operations result in a reduced number of reference samples, a higher detection loss is inevitable. Therefore, a censoring operation should only be performed when it is absolutely necessary.
The focus of this report is on detecting the presence of nonhomogeneous samples in the reference window prior to censoring, which is an important test that receives less attention in the literature. Based on the existence of rare events, a nonhomogeneity detection scheme designated as the mean-to-mean ratio (MMR) test is proposed. No a priori knowledge of the nonhomogeneity topology is assumed. Results obtained from Monte-Carlo simulations based on Rayleigh clutter and Swerling I target models are presented.
When being implemented in parallel with a CA-CFAR detector, target-like samples that are not detected by the CA-CFAR and yet have a deleterious effect on CA-CFAR performance can be detected with higher probabilities by the MMR test.
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