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CFAR detection in clutter with unknown correlation properties

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3 Author(s)
Raghavan, R.S. ; Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA ; Qiu, H.F. ; McLaughlin, D.J.

We develop a constant false-alarm rate (CFAR) approach for detecting a random N-dimensional complex vector in the presence of clutter or interference modeled as a zero mean complex Gaussian vector whose correlation properties are not known to the receiver. It is assumed that estimates of the correlation properties of the clutter/interference may be obtained independently by processing the received vectors from a set of reference cells. We characterize the detection performance of this algorithm when the signal to be detected is modeled as a zero-mean complex Gaussian random vector with unknown correlation matrix. Results show that for a prescribed false alarm probability and a given signal-to-clutter ratio (to be defined in the text), the detectability of Gaussian random signals depends on the eigenvalues of the matrix R c -1R s. The nonsingular matrix R c and the matrix R s are the correlation matrices of clutter-plus-noise and signal vectors respectively. It is shown that the "effective" fluctuation statistics of the signal to be detected is determined completely by the eigenvalues of the matrix R c -1R s. For example the signal to be detected has an effective Swerling II fluctuation statistics when all eigenvalues of the above matrix are equal. Swerling I fluctuation statistics results effectively when all eigenvalues except one are equal to zero. Eigenvalue distributions between these two limiting cases correspond to fluctuation statistics that lie between Swerling I and II models.<>

Published in:

Aerospace and Electronic Systems, IEEE Transactions on  (Volume:31 ,  Issue: 2 )