[1] Zeng X X. Research on recognition method of typical space target based on image[D]. Changsha: National University of Defense Technology(2015).

[2] Zhang J, Zhou X D, Zhang S F et al. Recognition of satellite targets based on combined invariant moments and artificial neural network[J]. Journal of Naval Aeronautical and Astronautical University, 23, 29-32(2008).

[3] Zeng W M, Wu Q X. 16(7): 21-24[J]. Jiang C S. Recognition method of aerial targets based on combined invariant moments. Electronics Optics & Control, 44, 97(2009).

[4] Wang X X, Yang Y S, Jing Z L. Spacetarget recognition based on improved kernel FCM[J]. Chinese Space Science and Technology, 32, 35-42(2012).

[5] Jiang F Y, Sun R, Zhang X D et al. Space target image categorization based on the second representation[J]. Journal of Electronics & Information Technology, 35, 1247-1251(2013).

[6] Ma J G, Zhao H Z, Li B G et al. Space target recognition algorithm based on two-dimensional wavelet transform[J]. Journal of National University of Defense Technology, 28, 57-61(2006).

[7] An M, Jiang Z G, Xu B. Recognitive method of space visible objects based on BFM algorithm[J]. Systems Engineering and Electronics, 31, 1075-1077(2009).

[8] Ren Y M, Zhang Y N, Li Y et al. A space target recognition method based on compressive sensing. [C]∥2011 Sixth International Conference on Image and Graphics, August 12-15, 2011, Hefei, Anhui, China. New York: IEEE, 582-586(2011).

[9] Cao W M, Feng H, Hu L L et al. Space target recognition based on biomimetic pattern recognition. [C]∥2009 First International Workshop on Database Technology and Applications, April 25-26, 2009, Wuhan, Hubei, China. New York: IEEE, 64-67(2009).

[10] Lee D D, Seung H S. Learning the parts of objects by non-negative matrix factorization[J]. Nature, 401, 788-791(1999). http://www.tandfonline.com/servlet/linkout?suffix=CIT0016&dbid=16&doi=10.1080%2F10485252.2017.1418869&key=10.1038%2F44565

[11] Li L, Zhang Y J. A survey on algorithms of non-negative matrix factorization[J]. Acta Electronica Sinica, 36, 737-743(2008).

[12] Ding M Y. Symmetry based two-dimensional principal component analysis and its application to face recognition[J]. Journal of Computer Applications, 28, 122-124(2008). http://en.cnki.com.cn/Article_en/CJFDTOTAL-JSJY200801041.htm

[13] Fang W T, Ma P, Cheng Z B et al. 2-dimensional projective non-negative matrix factorization and its application to face recognition[J]. Acta Automatica Sinica, 38, 1503-1512(2012).

[14] Gao H J, Pan C. Face recognition based on (2D) 2NMF and its improvement [J]. Journal of Computer Applications, 27, 1660-1662, 1666(2007).

[15] Li S Z, Hou X W, Zhang H J. Learning spatially localized, parts-based representation. [C]∥Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Parttern Recognition, December 8-14, 2001, USA. New York: IEEE, 207-212(2001).

[16] Hoyer P O. Non-negative matrix factorization with sparseness constraints[J]. The Journal of Machine Learning Research, 5, 1457-1469(2004). http://dl.acm.org/citation.cfm?id=1044709

[17] Wang F, Yang Y W, Tan S et al. Fault detection method based on sparse non-negative matrix factorization[J]. CIESC Journal, 66, 1798-1805(2015).

[18] Xu R, Zhao F, Li H F et al. Parallel measurement of spectral bidirectional reflectance distribution function of non-resolved space objects in laboratory[J]. Acta Photonica Sinica, 45, 0212002(2016).

[19] Wang X X. Research on recognition method of space target based on image features[D]. Shanghai: Shanghai Jiao Tong University, 5-29(2012).

[20] Wang M. Automatic recognition of space targets in complex background Changchun: Changchun Institute of Optics, Fine Mechanics and Physics,[D]. Chinese Academy of Sciences(2017).

[21] Gonzalez R C, Woods R E, Eddins S L[M]. Digital image processing using MATLAB, 367-368(2005).