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PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2011-07-06
Performance of the Adaptive Normalized Matched Filter Detector in Compound-Gaussian Clutter with Inverse Gamma Texture Model
By
Arezki Younsi,

    Dr. Arezki Younsi

    Ecole Militaire Polytechnique

    Algeria

    Homepage

M. Nadour

    Dr. M. Nadour

    Ecole Militaire Polytechnique

    Algeria

    Homepage

Progress In Electromagnetics Research B, Vol. 32, 21-38, 2011
doi:10.2528/PIERB11051905 | Google Scholar

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.
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Citation
Arezki Younsi, and M. Nadour, "Performance of the Adaptive Normalized Matched Filter Detector in Compound-Gaussian Clutter with Inverse Gamma Texture Model," Progress In Electromagnetics Research B, Vol. 32, 21-38, 2011.
doi:10.2528/PIERB11051905
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