Spacecraft telemetry data monitoring by dimensionality reduction techniques

Abstract

In this paper, we consider a "data-driven" anomaly detection framework for spacecraft systems using dimensionality reduction and reconstruction techniques. This method first learns a mapping from the original data space to a low dimensional space and its reverse mapping by applying linear or nonlinear dimensionality reduction algorithms to a normal training… (More)

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