A Deep Learning Anomaly Detection Framework for Satellite Telemetry with Fake Anomalies

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/ijae/volume-2022/1676933/figures/1676933.fig.003a.svgz" name="1676933.fig.003a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Before removal</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/ijae/volume-2022/1676933/figures/1676933.fig.003b.svgz" name="1676933.fig.003b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>After removal</td></tr></table>

<div>DDMN for fake anomalies’ removal: (a) values of 8 telemetries over time before fake anomalies’ removal; (b) values of 8 telemetries after fake anomalies’ removal.</div>

International Journal of Aerospace Engineering

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Figure 3

Figure 3: A Deep Learning Anomaly Detection Framework for Satellite Telemetry with Fake Anomalies 