Satellite data receiving system fault location based on GAN sequence

doi:10.7523/j.ucas.2021.0009

Abstract

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

CLC Number:

TN957

WANG Zhengsheng, LI Yalin, ZHANG Hongqun. Satellite data receiving system fault location based on GAN sequence[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(1): 109-118.

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