Distributed fuzzy maximum‐censored mean level detector‐constant false alarm rate detector based on voting fuzzy fusion rule. Issue 8 (1st October 2015)

• Record Type: Journal Article
• Authors: Gong, Shufeng; Pan, Minghai; Long, Weijun; Huang, Hao
• Is Part Of: IET radar, sonar & navigation. Volume 9:Issue 8(2015)
• Page Start: 1055
• Page End: 1062
• Publication Date: 2015-10-01
• Subjects: radar signal processing -- signal detection -- fuzzy set theory -- algebra; distributed fuzzy maximum‐censored mean level detector -- MX‐CMLD -- constant false alarm rate detector -- voting fuzzy fusion rule -- CFAR detection -- fuzzy space -- false alarm space -- reference cells -- fusion centre -- credibility measure -- global membership function -- homogeneous background -- nonhomogeneous background -- fuzzy algebraic product operator rule -- binary AND fusion rules -- binary OR fusion rules -- automatic radar target detection; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2015.0008
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : In this study, a new distributed fuzzy maximum‐censored mean level detector (MX‐CMLD) constant false alarm rate (CFAR) detection based on fuzzy space and voting fuzzy fusion rule is presented. In the distributed fuzzy MX‐CMLD CFAR detector, each sensor computes the value of the membership function to the false alarm space from the samples of the reference cells and transmits it to the fusion centre. The values are combined according to the voting fuzzy fusion rule and the credibility measure of each sensor to produce a global membership function to the false alarm space in the fusion centre. The simulation results show that the detection performance of the distributed fuzzy MX‐CMLD CFAR detector is better than the other fuzzy distributed detectors in homogeneous and non‐homogeneous background. Furthermore, the simulation results indicate that the fuzzy algebraic product operator rule gives better performance than the binary AND and the binary OR fusion rules.