Presented here is the problem of estimating the covariance. structure of a compound-Gaussian process and of its application to adaptive radar detection in clutter-dominated disturbance. The proposed estimator exploits the persymmetry property typical of Toeplitz covariance matrices and is based on secondary data, free of signal components,, and with the same covariance structure of the cell under test. We prove that, plugging the proposed covariance estimator into the normalized matched filter, leads to an adaptive detector which, irrespective of the shape of the clutter power spectral density, ensures the constant false alarm rate property with respect to both the clutter covariance matrix as well as the statistics of the texture. Finally, we show that. this adaptive receiver has an acceptable loss with respect to its nonadaptive counterpart and outperforms the previously proposed CFAR adaptive NMF (ANMF).
Exploiting persymmetry for CFAR detection in compound-Gaussian clutter
IEEE Transactions on Aerospace and Electronic Systems ; 39 , 2 ; 719-724
2003-04-01
539228 byte
Article (Journal)
Electronic Resource
English
CORRESPONDENCE - Exploiting Persymmetry for CFAR Detection in Compound-Gaussian Clutter
Online Contents | 2003
|PAPERS - Covariance Matrix Estimation for Adaptive CFAR Detection in Compound-Gaussian Clutter
Online Contents | 2002
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