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中国科学院大学学报 ›› 2023, Vol. 40 ›› Issue (1): 109-118.DOI: 10.7523/j.ucas.2021.0009

• 电子信息与计算机科学 • 上一篇    

基于GAN序列的卫星数据接收系统故障定位

王正晟1,2, 李亚林1, 张洪群1   

  1. 1. 中国科学院空天信息创新研究院, 北京 100094;
    2. 中国科学院大学电子电气与通信工程学院, 北京 100049
  • 收稿日期:2020-10-30 修回日期:2021-02-05 发布日期:2021-05-31
  • 通讯作者: 王正晟,E-mail:wangzs@aircas.ac.cn
  • 基金资助:
    中国科学院战略先导科技专项A类(XDA15000000)资助

Satellite data receiving system fault location based on GAN sequence

WANG Zhengsheng1,2, LI Yalin1, ZHANG Hongqun1   

  1. 1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
    2. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2020-10-30 Revised:2021-02-05 Published:2021-05-31

摘要: 现有的卫星数据接收系统故障定位方法受困于专家知识的难以获取。提出一种基于生成对抗网络(GAN)序列的故障定位方法GANseq。利用故障传播特性,将接收系统分解为M个信号处理单元(SPU),形成一个按照信号处理顺序排列的SPU序列;将故障定位问题转化为有序排列的M个异常检测子问题,其中第m个子问题为对前m个SPU的联合状态的异常检测;然后针对每个子问题采用基于GAN的状态参数检测模型,进而形成GAN序列;综合分析该序列在所有子问题上的检测结果以定位故障SPU。利用实际接收系统进行的实验证明所提出的GANseq不仅从数据驱动的角度完成了故障定位,而且在总体上降低了虚警率,并提高了定位精度。

关键词: 卫星数据接收系统, 故障定位, 生成对抗网络, 数据驱动

Abstract: Existing satellite data receiving system fault location methods suffer from the difficulty in obtaining expert knowledge. A generative adversarial network (GAN) sequence method called GANseq is proposed in this paper. According to the feature of fault propagation, the receiving system was first divided into M signal processing unit (SPU) to form a SPU sequence ranked by signal processing order (SPO). The fault location issue then was decomposed into ranked M anomaly detection sub-problems, where the mth sub-problem was the detection of the top m SPUs’ joint state. State parameters GANomaly-based detector was employed in each sub-problem, forming a GAN sequence. The detection results of this sequence on all sub-problems were analyzed to locate fault SPU. The experiment result from practical receiving system shows that GANseq can not only achieve fault location from data-driven perspective, but also reduce fault alarm rate and enhance accuracy level of fault location.

Key words: satellite data receiving system, fault location, GAN, data-driven

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