Abstract
A new constant false-alarm rate (CFAR) detector for non-Rayleigh data, based on fuzzy statistical normalization, is proposed. The proposed detector carries out the detection with two stages. The first stage of the fuzzy statistical normalization CFAR processor is background level estimation, based on fuzzy statistical normalization. The second stage is signal detection, based on the original data and the defuzzification normalized data. Performance comparisons are carried out to validate the superiority of the proposed CFAR detector.
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