[1] EL-DARYMLI K,GILL E W,MCGUIRE P,et al.Automatic target recognition in synthetic aperture radar imagery:a state-of-the-art review［J］.IEEE Access,2016,4:6014-6058.

[2] 王力.基于深度学习的SAR目标识别关键技术研究［D］.西安:西安电子科技大学, 2020.

[3] 董刚刚.基于单演信号的SAR图像目标识别技术研究［D］.长沙: 国防科学技术大学,2016.

[4] 谌华.SAR图像目标自动检测与识别方法研究［D］.北京: 中国科学院大学,2019.

[5] 王琛.基于深度学习的SAR目标分类与检测技术研究［D］.西安: 电子科技大学,2021.

[6] ANAGNOSTOPOULOS G C.SVM-based target recognition from synthetic aperture radar images using target region outline descriptors［J］.Nonlinear Analysis,2009,71(2):2934-2939.

[7] AMOON M,REZAI-RAD G A.Automatic target recognition of synthetic aperture radar (SAR) images based on optimal selection of Zernike moment features［J］.IET Computer Vision,2014,8(2):77-85.

[8] 付凡成.基于目标区域匹配的SAR目标识别方法［J］.电光与控制,2018,25(4):37-40.

[9] PAPSON S,NARAYANAN R M.Classification via the sha-dow region in SAR imagery［J］.IEEE Transactions on Aerospace and Electronic Systems,2012,40(8):969-980.

[10] MISHRA A K,MOTAUNG T.Application of linear and nonlinear PCA to SAR ATR［C］//The 25th International Conference Radioelektronika.Pardubice:IEEE,2015:349-354.

[11] 韩萍,王欢.结合KPCA和稀疏表示的SAR目标识别方法研究［J］.信号处理,2013,29(13):1696-1701.

[12] CUI Z Y,CAO Z J,YANG J Y,et al.Target recognition in synthetic aperture radar via non-negative matrix factorization［J］.IET Radar,Sonar and Navigation,2015,9(9):1376-1385.

[13] 李帅,许悦雷,马时平, 等.基于小波变换和深层稀疏编码的SAR目标识别［J］.电视技术,2014,38(13):31-35.

[14] 王源源.基于单演信号多重集典型相关分析的SAR目标识别方法［J］.电光与控制,2019,26(10):7-11,29.

[15] CHANG M,YOU X Q,CAO Z Y.Bidimensional empirical mode decomposition for SAR image feature extraction with application to target recognition［J］.IEEE Access,2019, 7:135720-135731.

[16] 丁柏圆,文贡坚,余连生, 等.属性散射中心匹配及其在SAR目标识别中的应用［J］.雷达学报,2017,6(2):157-166.

[17] DING B Y,WEN G J,ZHONG J R,et al.A robust similarity measure for attributed scattering center sets with application to SAR ATR［J］.Neurocomputing,2017,219:130-143.

[18] 郝岩,白艳萍,张校非.基于KNN的合成孔径雷达目标识别［J］.火力与指挥控制,2018,43(9):113-115, 120.

[19] 刘长清,陈博,潘舟浩,等.基于仿真SAR和SVM分类器的目标识别技术研究［J］.中国电子科学研究院学报,2016,11(3):257-262.

[20] LIU H C,LI S T.Decision fusion of sparse representation and support vector machine for SAR image target recognition［J］.Neurocomputing,2013,113:97-104.

[21] XING X W,JI K F,ZOU H X,et al.Sparse representation based SAR vehicle recognition along with aspect angle［J］.The Scientific World Journal,2014(3):834140.

[22] ZHANG L,TAO Z W,WANG B J.SAR image target re-cognition using kernel sparse representation based on reconstruction coefficient energy maximization ReLU［C］//IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP).Shanghai:IEEE,2016:2369-2373.

[23] CHEN S Z,WANG H P,XU F,et al.Target classification using the deep convolutional networks for SAR images［J］.IEEE Transactions on Geoscience and Remote Sensing,2016,54(8):4806-4817.

[24] XU Y,LU Y W.Adaptive weighted fusion:a novel fusion approach for image classification［J］.Neurocomputing, 2015,168:566-574.

[25] 王源源.一种基于多分辨率表示的SAR图像识别方法［J］.电光与控制,2020,27(10):31-36.