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DMSS: Decision Management System for Safer Spacecrafts

  • Olivier ParisotEmail author
  • Philippe Pinheiro
  • Patrik Hitzelberger
Conference paper
  • 228 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11803)

Abstract

The fast growing number of low earth orbit exploitation and deep space missions results in enormous volumes of telemetry data. In order to operate efficiently satellites constellations as well as spacecrafts, DMSS offers a self-learning visual platform for anomaly detection in telemetry data coming from embedded sensors. As use-case, the data of two space missions operated by the European Space Agency were analyzed: Mars Express and GAIA.

Keywords

Spacecraft telemetry Anomaly detection Visualization 

Notes

Acknowledgments

We would like to thank the Institute of Astronomy of KU Leuven, and especially Bart Vandenbussche, Pierre Royer and Joris De Ridder for the excellent and fruitful collaboration. We also wish to thank David Evans and Jose Martinez-Heras from the European Space Agency.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Olivier Parisot
    • 1
    Email author
  • Philippe Pinheiro
    • 1
  • Patrik Hitzelberger
    • 1
  1. 1.Luxembourg Institute of Science and Technology (LIST)Esch-sur-AlzetteLuxembourg

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