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Space Object Behavior Quantification and Assessment for Space Security

  • Moriba JahEmail author
Living reference work entry

Abstract

As the spacefaring community is well aware, the increasingly rapid proliferation of human-made objects in space, whether active satellites or debris, threatens the safe and secure operation of spacecraft and requires that we change the way we conduct business in space. The introduction of appropriate protocols and procedures to regulate the use of space is predicated on the availability of quantifiable and timely information regarding the behavior of resident space objects (RSO): the basis of space domain awareness (SDA). Yet despite six decades of space operations, and a growing global dependence on the services provided by space-based platforms, the population of Earth orbiting space objects is still neither rigorously nor comprehensively quantified, and the behaviors of these objects, whether directed by human agency or governed by interaction with the space environment, are inadequately characterized.

Key goals of advanced SDA are to develop a capability to predict RSO behavior, extending SDA beyond its present paradigm of catalog maintenance and forensic analysis, and to arrive at a comprehensive physical understanding of all of the inputs that affect the motion of RSOs. Solutions to these problems require transdisciplinary engagement that combines space surveillance data with other information, including space object databases and space environmental data, to help decision-making processes predict, detect, and quantify threatening and hazardous space domain activity.

References

  1. Bever M, Delande E, Jah M (2019) Outer probability measures for first and second order uncertainty in the space domain. IAA-AAS SciTech-040, Moscow, Russia, JuneGoogle Scholar
  2. Delande E, Houssineau J, Jah M (2018) Physics and human-based information fusion for improved resident space object tracking. Adv Space Res 62(7):1800–1812.  https://doi.org/10.1016/j.asr.2018.06.033. ElsevierCrossRefGoogle Scholar
  3. DeMars KJ, Bishop RH, Jah MK (2013) Entropy-based approach for uncertainty propagation of nonlinear dynamical systems. J Guid Control Dyn 36(4):1047–1057.  https://doi.org/10.2514/1.58987CrossRefGoogle Scholar
  4. Stauch J, Bessell T, Rutten M, Baldwin J, Jah M, Hill K (2017) Joint Probabilistic Data Association and smoothing applied to multiple space object tracking. J Guid Control Dyn (Special Issue on Space Domain Awareness):1–15. http://arc.aiaa.org/doi/abs/10.2514/1.G002230

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Aerospace Engineering & Engineering MechanicsThe University of Texas at AustinAustinUSA

Section editors and affiliations

  • Maarten Adriaensen
    • 1
  1. 1.European Space AgencyParisFrance

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