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

Wang Xia1, Xu Can2、*, Zhang Feng1, and Li Peng1
Author Affiliations
  • 1Department of Graduate Management, Space Engineering University, Beijing 101416, China
  • 2Department of Space Command, Space Engineering University, Beijing 101416, China
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    [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).

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    [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

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    Paper Information

    Category: Measurement and metrology

    Received: Sep. 2, 2019

    Accepted: --

    Published Online: Mar. 12, 2020

    The Author Email: Can Xu (627176089@qq.com)

    DOI:10.3788/CJL202047.0304005

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