Conjugate unscented transformation based orbital state estimation and sensor tasking for efficient space surveillance

Nagavenkat Adurthi, Manoranjan Majji, Puneet Singla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper presents a novel sensor management framework to effectively monitor Resident Space Objects (RSOs) for Space Situational Awareness (SSA) applications. The central idea of the proposed methodology is to make use of information geometry for the characterization of current state of knowledge (situational awareness), which is used for the purpose of optimal sensor management. Recently developed Conjugate Unscented Transformation (CUT) method has been exploited to accurately and efficiently propagate non-Gaussian orbit state uncertainty and compute information metrics. Finally, an optimization problem is posed to solve for optimal sensing action while accounting for orbital state uncertainty. Numerical simulations are performed which illustrate the effectiveness of the proposed methodology in comparison to conventional methods which assume orbital density function to be Gaussian.

Original languageEnglish (US)
Title of host publicationAIAA/AAS Astrodynamics Specialist Conference 2014
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Print)9781624103087
StatePublished - Jan 1 2014
EventAIAA/AAS Astrodynamics Specialist Conference 2014 - San Diego, CA, United States
Duration: Aug 4 2014Aug 7 2014

Publication series

NameAIAA/AAS Astrodynamics Specialist Conference 2014

Other

OtherAIAA/AAS Astrodynamics Specialist Conference 2014
CountryUnited States
CitySan Diego, CA
Period8/4/148/7/14

Fingerprint

Space surveillance
space surveillance
situational awareness
state estimation
State estimation
methodology
orbitals
sensors
Sensors
Probability density function
Orbits
orbits
optimization
Geometry
Computer simulation
geometry
simulation
Uncertainty

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Astronomy and Astrophysics

Cite this

Adurthi, N., Majji, M., & Singla, P. (2014). Conjugate unscented transformation based orbital state estimation and sensor tasking for efficient space surveillance. In AIAA/AAS Astrodynamics Specialist Conference 2014 (AIAA/AAS Astrodynamics Specialist Conference 2014). American Institute of Aeronautics and Astronautics Inc..
Adurthi, Nagavenkat ; Majji, Manoranjan ; Singla, Puneet. / Conjugate unscented transformation based orbital state estimation and sensor tasking for efficient space surveillance. AIAA/AAS Astrodynamics Specialist Conference 2014. American Institute of Aeronautics and Astronautics Inc., 2014. (AIAA/AAS Astrodynamics Specialist Conference 2014).
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Adurthi, N, Majji, M & Singla, P 2014, Conjugate unscented transformation based orbital state estimation and sensor tasking for efficient space surveillance. in AIAA/AAS Astrodynamics Specialist Conference 2014. AIAA/AAS Astrodynamics Specialist Conference 2014, American Institute of Aeronautics and Astronautics Inc., AIAA/AAS Astrodynamics Specialist Conference 2014, San Diego, CA, United States, 8/4/14.

Conjugate unscented transformation based orbital state estimation and sensor tasking for efficient space surveillance. / Adurthi, Nagavenkat; Majji, Manoranjan; Singla, Puneet.

AIAA/AAS Astrodynamics Specialist Conference 2014. American Institute of Aeronautics and Astronautics Inc., 2014. (AIAA/AAS Astrodynamics Specialist Conference 2014).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - This paper presents a novel sensor management framework to effectively monitor Resident Space Objects (RSOs) for Space Situational Awareness (SSA) applications. The central idea of the proposed methodology is to make use of information geometry for the characterization of current state of knowledge (situational awareness), which is used for the purpose of optimal sensor management. Recently developed Conjugate Unscented Transformation (CUT) method has been exploited to accurately and efficiently propagate non-Gaussian orbit state uncertainty and compute information metrics. Finally, an optimization problem is posed to solve for optimal sensing action while accounting for orbital state uncertainty. Numerical simulations are performed which illustrate the effectiveness of the proposed methodology in comparison to conventional methods which assume orbital density function to be Gaussian.

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Adurthi N, Majji M, Singla P. Conjugate unscented transformation based orbital state estimation and sensor tasking for efficient space surveillance. In AIAA/AAS Astrodynamics Specialist Conference 2014. American Institute of Aeronautics and Astronautics Inc. 2014. (AIAA/AAS Astrodynamics Specialist Conference 2014).