Satellite Early Anomaly Detection Using an Advanced Transformer Architecture for Non-Stationary Telemetry Data-Reference-Cited by-同舟云学术

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Satellite Early Anomaly Detection Using an Advanced Transformer Architecture for Non-Stationary Telemetry Data

Published:2024-02 Issue:1 Volume:70 Page:4213-4225
ISSN:0098-3063
Container-title:IEEE Transactions on Consumer Electronics
language:
Short-container-title:IEEE Trans. Consumer Electron.

Author:

Zhao Haotian¹^ORCID,Qiu Shi¹,Yang Jianan¹^ORCID,Guo Jinsheng¹,Liu Ming¹^ORCID,Cao Xibin¹^ORCID

Affiliation:

1. School of Aeronautics, Harbin Institute of Technology, Harbin, China

Funder

Science Center Program of National Natural Science Foundation of China

National Natural Science Foundation of China

Heilongjiang Touyan Team; and

Guangdong Major Project of Basic and Applied Basic Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/30/10510045/10413519.pdf?arnumber=10413519

Reference40 articles.

1. Satellite Telemetry Data Anomaly Detection Using Causal Network and Feature-Attention-Based LSTM

2. GeoTrackNet--A Maritime Anomaly Detector Using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection

3. Applications of Deep Learning Neural Networks to Satellite Telemetry Monitoring

4. MAG: A Novel Approach for Effective Anomaly Detection in Spacecraft Telemetry Data

5. Satellite Micro Anomaly Detection Based on Telemetry Data

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