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Abstract:We propose a constant false alarm rate (CFAR) algorithm for moving target detection in synthetic aperture radar (SAR) images based on the spreading characteristics of interferograms on the magnitude-phase (M-P) plane. This method is based on the observation that, in practice, both moving and stationary targets along with clutter are located at different regions in the M-P plane, and hence reasonable partitions of the M-P plane can help in detecting moving targets. To ensure efficient CFAR detection and to resolve the effect of factors that influence detection results, the proposed algorithm is divided into three distinct stages: coarse detection, fine detection, and post-processing. First, to accurately describe the statistical behavior of clutter, a global censoring strategy, called coarse detection, is introduced to adaptively eliminate the influences of the moving and stationary target points from the given data. Then, to acquire fine detection results, a novel CFAR detector is developed on the basis of the fits of a known theoretical M-P joint probability density function (PDF) against the two-dimensional (2-D) histogram of the censored clutter. The joint PDF's projected contour line that satisfies the desirable probability of false alarm (PFA) corresponds to the required threshold of detection in the M-P plane. Finally, two filters, the magnitude and phase filters, are applied to reduce the false alarms generated from the

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