Contrastive Learning with Prototype-Based Negative Mixing for Satellite Telemetry Anomaly Detection

Contrastive Learning with Prototype-Based Negative Mixing for Satellite Telemetry Anomaly Detection

Telemetry data are the most important basis for ground operators to assess the status of satellites in orbit, and telemetry data-based anomaly detection has become a key tool to improve the reliability and safety of spacecrafts. Recent research on anomaly detection focuses on constructing a normal p...

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Bibliographic Details
Main Authors: Guohang Guo, Tai Hu, Taichun Zhou, Hu Li, Yurong Liu
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Sensors
Subjects:
telemetry data
anomaly detection
contrastive learning
negative mixing
Online Access:https://www.mdpi.com/1424-8220/23/10/4723

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