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• W2058657806 abstract "The authors develop the theory of CA-CFAR (cell-averaging constant false-alarm rate) detection using multiple sensors and data fusion, where detection decisions are transmitted from each CA-CFAR detector to the data fusion center. The overall decision is obtained at the data fusion center based on some k out of n fusion rule. For a Swerling target model I embedded in white Gaussian noise of unknown level, the authors obtain the optimum threshold multipliers of the individual detectors. At the data fusion center, they derive an expression for the overall probability of detection while the overall probability of false alarm is maintained at the desired value for the given fusion rules. An example is presented showing numerical results.< <ETX xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>></ETX>" @default.
• W2058657806 created "2016-06-24" @default.
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• W2058657806 date "1989-03-01" @default.
• W2058657806 modified "2023-10-16" @default.
• W2058657806 title "Decentralized CFAR signal detection" @default.
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• W2058657806 doi "https://doi.org/10.1109/7.18676" @default.
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