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《Computer Simulation》 2008-09
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A Novel CFAR Detector Based on Unbiased Minimum-Variance Estimation and Cell Averaging

QU Chao,HAO Cheng-peng,YANG Shu-yuan(Institute of Acoustics,Chinese Academy of Sciences,Beijing 100080,China)  
The technique of combining auto-detection with CFAR is frequently used in radar system,to get a predictable target detection probability at some false alarm rate cost in time-varying clutter situations.A new CFAR detector(MUMCA-CFAR) based on unbiased minimum-variance estimation and cell averaging is presented in this paper.It takes the sum of UMVE of leading window and CA estimation of lagging window as a global noise power estimation.Under SwerlingII assumption,the analytic expressions of false alarm probability and detection probability in homogeneous background are derived,and the analytic expression of detection probability in multiple target situations is also derived.In contrast to other detectors,the MOSUM-CFAR detector has fairly well detection performance in both homogeneous background and multiple target situations.
【Fund】: 国防十一五预研基金资助课题(1010602010401)
【CateGory Index】: TN957.5
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