Abstract
Constant false alarm rate (CFAR) detection in synthetic aperture radar (SAR) is the first step in most ATR and image exploitation systems. In this paper several CFAR algorithms and their implementation on a 1-D SIMD array processor are investigated. We primarily focus on CFAR algorithms using the Weibull clutter model, but algorithms assuming K-distributed clutter should have similar implementations and runtimes. We show that high resolution SAR requires reference windows much larger than those used in traditional search radars, which permits fast moment based estimation instead of the computationally intensive maximum likelihood parameter estimates. We also extend a fast median filtering algorithm to the order statistic and censored CFAR algorithms. The running times of the CFAR algorithms are listed along with detection results using SAR imagery from the Northrop-Grumman TESAR sensor onboard the Predator unmanned aerial vehicle.
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