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• W2109396519 abstract "In the present paper, we deal with the performance analysis of the Adaptive Normalized Matched Filter (ANMF) detector in compound-Gaussian clutter with inverse gamma texture model and unknown covariance matrix. First, the maximum likelihood estimate (MLE) of the covariance matrix for this clutter model is derived. The MLE is then plugged into the ANMF test and compared to the well known normalized sample covariance matrix estimate (NSCM) and the approximate maximum likelihood estimate (AML). The performance in terms of CFAR behavior and detection probability is evaluated in the presence of simulated clutter and real sea clutter data, which is collected by the McMaster IPIX radar." @default.
• W2109396519 created "2016-06-24" @default.
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• W2109396519 date "2011-01-01" @default.
• W2109396519 modified "2023-09-27" @default.
• W2109396519 title "PERFORMANCE OF THE ADAPTIVE NORMALIZED MATCHED FILTER DETECTOR IN COMPOUND-GAUSSIAN CLUTTER WITH INVERSE GAMMA TEXTURE MODEL" @default.
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• W2109396519 doi "https://doi.org/10.2528/pierb11051905" @default.
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