Decision fusion of CNN and SRC with application to SAR target recognition

Jianhua Lu

doi:10.3788/IRLA20210421

[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] P J Zhao, K Gan. SAR target recognition based on hierarchical decision fusion of complementary features. Electronics Optics & Control, 25, 28-32(2018).

[4] Q Xie, H Zhang. Multi-level SAR image enhancement based on regularization with application to target recognition. Journal of Electronic Measurement and Instrumentation, 32, 157-162(2018).

[5] G J Wen, G Q Zhu, H C Yin, et al. SAR ATR based on 3D parametric electromagnetic scattering model. Journal of Radar, 6, 115-135(2017).

[6] 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).

[7] 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).

[8] P Han, H Wang. Research on the synthetic aperture radar target recognition based on KPCA and sparse representation. Journal of Signal Processing, 29, 1696-1701(2013).

[9] 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).

[10] 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).

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

[12] Z C Liu, B D Qu. Application of complex bidimensional empirical mode decomposition in SAR target recognition. Infrared and Laser Engineering, 50, 20200309(2021).

[13] 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).

[14] T B Wu, J B Xia, Y Y Huang, et al. Target recognition method of SAR images based on cascade decision fusion of SVM and SRC. Journal of Henan Polytechnic University (Natural Science), 39, 118-124(2020).

[15] 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.

[16] H Zhang, X L Zuo, Y Huang, et al. Feature selection based on the correlation of sparse coefficient vectors with application to SAR target recognition. Laser & Optoelectronics Progress, 57, 263-270(2020).

[17] J S Tang, S H Qing. SAR images recognition based on sparse coefficients optimal local reconstruction. Journal of Detection & Control, 43, 69-75, 80(2021).

[18] 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).

[19] 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).

[20] J Ding, B Chen, H W Liu, et al. Convolutional neural network with data augmentation for SAR target recognition. IEEE Geoscience and Remote Sensing Letters, 13, 1-5(2016).

[21] Y Yan. Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition. Journal of Electronic Imaging, 27, 023024(2018).

[22] L Z Jin, J J Chen, X G Peng. Reliability analysis for decision fusion and its application in target recognition of SAR images. Telecommunication Engineering, 59, 409-414(2019).