[1] K EL-Darymli, E W Gill, P Mcguire, et al. Automatic target recognition in synthetic aperture radar imagery: a state-of-the-art review. IEEE Access, 4, 6014-6058(2016).

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

[3] S Papson, R M Narayanan. Classification via the shadow region in SAR Imagery. IEEE Transactions on Aerospace and Electronic System, 40, 969-980(2012).

[4] [4] Mishra A K, Motaung T. Application of linear nonlinear PCA to SAR ATR[C] Radioelektronika, 2015: 16.

[5] W H LI, J G Wang. SAR images target recognition based on bilateral two-dimensional principal component analysis and probabilistic neural network ensemble. Journal of CAEIT, 9, 401-407(2014).

[6] Z Y Cui, Z J Cao, J Y Yang, et al. Target recognition in synthetic aperture radar via non-negative matrix factorization. IET Radar, Sonar and Navigation, 9, 1376-1385(2015).

[7] G G Dong, G Y Kuang, N Wang, et al. SAR target recognition via joint sparse representation of monogenic signal. IEEE Journal of Selected Topics Applied Earth Observation and Remote Sensing, 8, 3316-3328(2015).

[8] Y Y Wang. SAR target recognition based on monogenic features via multiset canonical correlation analysis. Electronics Optics & Control, 26, 7-11,29(2019).

[9] X W Liu, J J Lei, Y P Wu. Synthetic aperture radara target recognition based on bidimensional empirical mode decomposition. Laser and Optoelectronics Progress, 57, 051004(2020).

[10] G Y Zhou, B Q Liu, D Zhang. Target recognition in SAR images based on variational mode decomposition. Remote Sensing for Land and Resources, 32, 33-39(2020).

[11] R Zhang, J Hong, F Ming. Full polarimetry SAR ATR algorithm based on polarimetry similarity. Foreign Electronic Measurement Technology, 29, 24-27(2010).

[12] B Y Ding, G J Wen, L S Yu, et al. Matching of attributed scattering center and its application to synthetic aperture radar automatic target recognition. Journal of Radar, 6, 157-166(2017).

[13] B Y Ding, G J Wen, J R Zhong, et al. A robust similarity measure for attributed scattering center sets with application to SAR ATR. Neurocomputing, 219, 130-143(2017).

[14] Y Hao, Y P Ai, Y F Zhang. Synthetic aperture radar target recognition based on KNN. Fire Control & Command Control, 43, 113-115, 120(2018).

[15] C Q Liu, B Chen, Z H Pan, et al. Research on Target Recognition Technique via Simulation SAR and SVM classifier. Journal of CAEIT, 11, 257-262(2016).

[16] H C Liu, S T Li. Decision fusion of sparse representation and support vector machine for SAR image target recognition. Neurocomputing, 113, 97-104(2013).

[17] [17] Thiagaraianm J, Ramamurthy K, Knee P P, et al. Sparse representations f automatic target classification in SAR images [C]4th Communications, Control Signal Processing, 2010: 1–4.

[18] J S Tang, S H Qin. SAR target recognition based on sparse coefficients optimal local reconstruction. Journal of Detection & Control, 43, 69-75(2013).

[19] H Zhang, X L Zuo, Y Huang. Feature selection based on the correlation of sparse coefficient vectors with application to SAR target recognition. Laser and Optoelectronics Progress, 57, 141029(2020).

[20] S Z Chen, H P Wang, F Xu, et al. Target classification using the deep convolutional networks for SAR images. IEEE Transactions on Geoscience and Remote Sensing, 54, 4806-4817(2016).

[21] P P Zhang, H B Luo, M R Ju, et al. An improved capsule and its application in target recognition of SAR images. Infrared and Laser Engineering, 49, 20201010(2020).

[22] Y Xu, Y Gu, D L Peng, et al. SAR ATR based on disentangled representation learning generative adversarial networks and support vector machine. Optics and Precision Engineering, 28, 727-735(2020).

[23] J L Peng, Q Li, A A El-latif, et al. Linear discriminant multi-set canonical correlations analysis (LDMCCA): an efficient approach for feature fusion of finger biometrics. Multimedia Tools and Applications, 74, 4469-4486(2015).

[24] A K Qiu, J G Zhu. Multi-set canonical correlations analysis based on ensemble learning. Computer Engineering and Applications, 53, 162-169(2017).

[25] H C Zhang, N M Nasrabadi, Y Zhang, et al. Multi-view automatic target recognition using joint sparse representation. IEEE Transactions on Aerospace and Electronic Systtems, 48, 2481-2497(2012).

[26] [26] Ding B Y, Wen G J, Ye F, et al. Feature extraction based on 2 D compressive sensing f SAR automatic target recognition [C]EUCAP, 2017: 12191223.

[27] J B Wu, Z W Lu, Y R Guang, et al. SAR target recognition using feature fusion by 2D compressive sensing with multiple random projection matrices. Infrared and Laser Engineering, 50, 20200531(2021).