Aiming at the performance limitations of the cell-averaged constant false alarm detector(CA-CFAR)in the presence of multi-target interference and clutter fringe effects,a constant false alarm detector(MCA-CFAR)based on the minimum selection cell in the sub-reference window is proposed.The performance of the detector is significantly improved by selecting the smallest cell in the sub-reference cell,and the detection probability,false alarm rate and detection threshold are derived in detail in the context of Rayleigh distribution.To further optimize the performance,a fuzzy logic fusion detector(FUMCA-CFAR)is designed,which uses two sensors to compute the spatial affiliation function values and fuses them by four rules,namely,algebraic sum,alge-braic product,MAX,and MIN,to achieve a smooth output and reduce the loss of target information.Simulation experiments show that the FUMCA-CFAR detector based on algebraic sum fusion exhibits excellent detection performance and anti-jamming ability in both uniform and non-uniform backgrounds.
cell-averaged constant false alarm detectorclutter edge effectfuzzy fusionspatial affiliation function value
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