Affiliation of Author(s):电子信息工程学院

Journal:Proc SPIE Int Soc Opt Eng

Abstract:Since a lot of speckles in SAR images, there are a lot of uncertainty in SAR image. It brings a lot of difficulty to the targets detection. Fuzzy theory is a mathematical method used to reduce this uncertainty. A new FSII-CFAR detector is proposed, which is improved intelligent iterative CFAR detection by searching a better fitting distribution model of SAR image background based on fuzzy logic. The best fitting distribution model of background data is decided by the membership value of fuzzy clustering criterion (FCC). Compared with traditional fitting criterion, the results of the FCC improve the detection rate of CFAR. Because the fitting results are more approximated to SAR image background, the simulation results show that the FSII-CFAR detector can make the detection rate reach more than 80% in complex background. © 2018 SPIE.

ISSN No.:0277-786X

Translation or Not:no

Date of Publication:2018-01-01

Co-author:zsq,Henry, Leung

Correspondence Author:Katherine Kong