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JOURNAL OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES
This paper proposes a novel "knowledge-free" anomaly detection method for spacecraft based on regression techniques. This method learns a linear or nonlinear probabilistic regression model in the learning phase by applying a regression technique to a massive telemetry data of spacecraft, and then monitors the real-time telemetry data using the constructed model. This approach can be seen as adaptive limit-checking because it sequentially predicts proper envelop of a target time-series based ondoi:10.2322/jjsass.54.312 fatcat:sstwrt6ycnb3hexxzmhlq57spa