基于神经网络模式识别的航天器在轨遥测状态实时识别方法

Xiaopeng Zhang, Wei Qin, Haixiao Zhuang, Yongfu Guo, Ping Yang, Hongbo Han, Yufei Liu, Bing Chen, Zhixin Chen
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引用次数: 1

摘要

针对在轨航天器状态实时识别问题,以太阳帆板遥测数据为分析对象,提出了一种基于神经网络模式识别的航天器在轨状态实时识别方法。该方法以每个信号周期为单位,进行遥测在轨识别。通过大量数据试验,验证了该方法的有效性,满足了航天器异常状态在轨监测的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Real-Time Recognition Method for Telemetry Status of Spacecraft in-Orbit Based on Neural Network Pattern Recognition
Aiming at the problem of real-time recognition of in-orbit spacecraft state, a real-time recognition method for spacecraft state in-orbit based on neural network pattern recognition is proposed by taking the telemetry data of solar array as the analysis object. This method uses every signal period as a unit to conduct telemetry in-orbit identification. Through a large number of data tests, the results verify the effectiveness of the method and meet the requirements of in-orbit monitoring for spacecraft with abnormal state.
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