SAR ATR based on displacement- and rotation-insensitive CNN

Remote Sensing Letters

Volumn 7, Issue 9, 2016, Pages 895-904

  Du, Kangning ^a   Deng, Yunkai ^a   Wang, Robert ^a   Zhao, Tuan ^a   Li, Ning ^a  

^a INSTITUTE OF ELECTRONICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; AUTOMATIC TARGET RECOGNITION; CLASSIFICATION (OF INFORMATION); NEURAL NETWORKS; ROTATION; SYNTHETIC APERTURE RADAR;

CLASSIFICATION ACCURACY; CONVOLUTIONAL NEURAL NETWORK; HEADING DIRECTIONS; PRECISE LOCATIONS; REALISTIC APPLICATIONS; ROTATION ANGLES; STATIONARY TARGETS; TRAINING DATASET;

RADAR TARGET RECOGNITION;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; AUTOMATION; DATA SET; IMAGE ANALYSIS; IMAGE CLASSIFICATION; ROTATION;

EID: 84976407137     PISSN: 2150704X     EISSN: 21507058     Source Type: Journal    
DOI: 10.1080/2150704X.2016.1196837     Document Type: Article

References (14)

1. M.Abadi,, A.Agarwal, P.Barham, E.Brevdo, Z.Chen, C.Citro, G.S.Corrado, et al. 2015. “Tensorflow: Large-Scale Machine Learning on Heterogeneous Systems, 2015.” Software available from tensorflow.org.
2. S.Chen,, and H.Wang. 2014. “SAR Target Recognition Based on Deep Learning.” 2014 International Conference on Data Science and Advanced Analytics (DSAA), Shanghai, October 30–November 1, 541–547.
3. J.Ding,, B.Chen, H.Liu, and M.Huang. 2016. “Convolutional Neural Network with Data Augmentation for SAR Target Recognition.” IEEE Geoscience and Remote Sensing Letters 13 (3): 364–368.
4. X.Glorot,, A.Bordes, and Y.Bengio. 2010. “Deep Sparse Rectifier Neural Networks.” Jmlr W & Cp 15: 315–323.
5. I.Goodfellow,, A.Courville, and Y.Bengio. 2015. Deep Learning. Cambridge, MA: MIT Press. Book in preparation for MIT Press.
6. S.Ioffe,, and C.Szegedy. 2015. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. arXiv preprint arXiv:1502.03167. Ithaca, NY: Cornell University.
7. L.Jia,, F.Ning, X.Yong-Jun, and B.-F.Wang. 2016. “Multi-Scale Feature-Based Fuzzy-Support Vector Machine Classification Using Radar Range Profiles.” IET Radar, Sonar & Navigation 10 (2): 370–378. doi:10.1049/iet-rsn.2015.0244.
8. Z.Jianxiong,, S.Zhiguang, C.Xiao, and F.Qiang. 2011. “Automatic Target Recognition of SAR Images Based on Global Scattering Center Model.” IEEE Transactions on Geoscience and Remote Sensing 49 (10): 3713–3729. doi:10.1109/TGRS.2011.2162526.
9. D.P.Kingma,, and J.L.Ba. 2015. “Adam: A Method for Stochastic Optimization.” ICLR 2015, San Diego, CA, May 7–9.
10. A.Krizhevsky,, I.Sutskever, and G.E.Hinton. 2012. “ImageNet Classification with Deep Convolutional Neural Networks.” In Advances in Neural Information Processing Systems 25, edited by F.Pereira, C.J.C.Burges, L.Bottou, and K.Q.Weinberger, 1097–1105. Red Hook, NY: Curran Associates. Lake Tahoe, NV, December 3–6.
11. J.-I.Park,, S.-H.Park, and K.-T.Kim. 2013. “New Discrimination Features for SAR Automatic Target Recognition.” IEEE Geoscience and Remote Sensing Letters 10 (3): 476–480. doi:10.1109/LGRS.2012.2210385.
12. S.Wagner, 2014. “Combination of Convolutional Feature Extraction and Support Vector Machines for Radar ATR.” 2014 17th International Conference on Information Fusion (FUSION), Salamanca, July 7–10, 1–6.
13. S.Wagner, 2015. “Morphological Component Analysis in SAR Images to Improve the Generalization of ATR Systems.” 2015 3rd International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), Pisa, June 16–19, 46–50.
14. L.Xuan,, L.Chunsheng, W.Pengbo, M.Zhirong, and X.Huaping. 2015. “SAR ATR Based on Dividing CNN into CAE and SNN.” 2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Singapore, September 1–4, 676–679.