Aircraft Detection for HR SAR Images in Non-homogeneous Background Using GGMD-Based Modeling  

作　　者：HU Hao HUANG Lanqing YU Wenxian 

机构地区：[1]Shanghai Key Laboratory of Intelligent Sensing and Recognition, Shanghai Jiao Tong University

出　　处：《Chinese Journal of Electronics》2019年第6期1271-1280,共10页电子学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.61331015)

摘　　要：In the problem of aircraft detection for High resolution(HR)Synthetic aperture radar(SAR)images,the background areas commonly contain multiple land cover types,such as runways and grassland.The conventional Constant false alarm rate(CFAR)detection in these non-homogeneous backgrounds with homogeneous assumption leads to unreliable detection results.This paper constructs a one-stage detection method based on the Generalized gamma mixture distribution(GGMD),which is regarded as a competitive and applicable model for combining the advantages of the Generalized gamma distribution(GGD)and the Finite mixture model(FMM).In order to evaluate the availability of the proposed algorithm,HR SAR images for aircraft detection from different product types and with various resolutions are examined.Compared with the CFAR algorithms based on the Gamma distribution,the GGD,and the gamma mixture distribution,the proposed algorithm demonstrates its availability and effectiveness for aircraft detection in HR SAR images in non-homogeneous background.In the problem of aircraft detection for High resolution(HR) Synthetic aperture radar(SAR)images, the background areas commonly contain multiple land cover types, such as runways and grassland. The conventional Constant false alarm rate(CFAR) detection in these non-homogeneous backgrounds with homogeneous assumption leads to unreliable detection results. This paper constructs a one-stage detection method based on the Generalized gamma mixture distribution(GGMD),which is regarded as a competitive and applicable model for combining the advantages of the Generalized gamma distribution(GGD) and the Finite mixture model(FMM).In order to evaluate the availability of the proposed algorithm, HR SAR images for aircraft detection from different product types and with various resolutions are examined. Compared with the CFAR algorithms based on the Gamma distribution, the GGD, and the gamma mixture distribution, the proposed algorithm demonstrates its availability and effectiveness for aircraft detection in HR SAR images in non-homogeneous background.

关 键 词：Constant false ALARM rate(CFAR) Generalized gamma mixture distribution(GGMD) EXPECTATION maximization(EM) Synthetic aperture radar(SAR) 

分 类 号：TN[电子电信]