Constant False Alarm Rate (CFAR) processing of Synthetic Aperture Radar (SAR) images facilitates target detection in spatially varying background clutter. The traditional Rayleigh distribution does not appear to be a good choice for modeling the natural terrain backscatter in high resolution SAR. We use the Weibull and K distributions to model clutter since they seem to fit observed data better and also include the Rayleigh distribution as a special case. The Cell Averaged CFAR technique works well in situations where a single, small target is present in locally homogeneous clutter. The Order Statistic CFAR is more useful for larger targets and in multiple target situations. Comparisons are made between the various CFAR techniques by applying them to real, high-resolution SAR images, obtained from the MIT Lincoln Laboratory.<>
Non-Gaussian CFAR techniques for target detection in high resolution SAR images
Proceedings of 1st International Conference on Image Processing ; 1 ; 910-914 vol.1
1994-01-01
351573 byte
Conference paper
Electronic Resource
English
Non-Gaussian CFAR Techniques for Target Detection in High Resolution SAR Images
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