Chinese Journal of Lasers, Volume. 47, Issue 3, 304005(2020)
Anomaly Detection Method for Working Status of Low-Orbit Space Objects Based on Photometric Data
[1] Wan M, Wu C, Ying Z et al. A pre-research on GWAC massive catalog data storage and processing system[J]. Astronomical Research & Technology, 13, 373-381(2016).
[2] Linares R, Furfaro R. Space object classification using deep convolutional neural networks. [C]∥2016 19th International Conference on Information Fusion (FUSION), July 5-8, 2016, Heidelberg, Germany. New York: IEEE, 16206458(2016).
[3] Furfaro R, Linares R, Reddy V. Space objects classification via light-curve measurements: deep convolutional neural networks and model-based transfer learning. [C]∥AMOS Technologies Conference, September 11-14, 2018, Wailea, Maui, Hawaii. [S.l.: s.n.](2018).
[4] Regan D. Modular neural network tasking of space situational awareness systems. [C]∥The Advanced Maui Optical and Space Surveillance Technologies Conference, September 11-14, 2018, Wailea, Maui, Hawaii. [S.l.: s.n.](2018).
[5] Xu C, Li Z, Zhang F. A GEO satellite working state detection method based on photometric characteristics[J]. Proceedings of SPIE, 10815, 1081511(2018).
[6] Qi J, Moran M S, Cabot F et al. Normalization of sun/view angle effects using spectral albedo-based vegetation indices[J]. Remote Sensing of Environment, 52, 207-217(1995).
[9] Keogh E J, Pazzani M J. Derivative dynamic time warping. [C]∥Proceedings of the 2001 SIAM International Conference on Data Mining, April 5-7, 2001, Chicago, IL, USA. [S.l.: s.n.](2001).
[10] Li Z X, Guo J S, Wang Y et al. Filtering search method for DTW distance[J]. Control and Decision, 33, 1277-1281(2018).
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Wang Xia, Xu Can, Zhang Feng, Li Peng. Anomaly Detection Method for Working Status of Low-Orbit Space Objects Based on Photometric Data[J]. Chinese Journal of Lasers, 2020, 47(3): 304005
Category: Measurement and metrology
Received: Sep. 2, 2019
Accepted: --
Published Online: Mar. 12, 2020
The Author Email: Can Xu (627176089@qq.com)