Resident space object shape inversion via Adaptive Hamiltonian Markov Chain Monte Carlo

Richard Linares; John L. Crassidis

Resident space object shape inversion via Adaptive Hamiltonian Markov Chain Monte Carlo

Richard Linares, John L. Crassidis

Aerospace Engineering and Mechanics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

This paper presents a method to determine the shape of a space object while simultaneously recovering the observed space object's inertial orientation. This paper employs an Adaptive Hamiltonian Markov Chain Monte Carlo estimation approach, which uses light curve data to infer the space object's orientation, shape, and surface parameters. This method is shown to work well for relatively high dimensions and non-Gaussian distributions of the light curve inversion problem.

Original language	English (US)
Title of host publication	Spaceflight Mechanics 2016
Editors	Martin T. Ozimek, Renato Zanetti, Angela L. Bowes, Ryan P. Russell, Martin T. Ozimek
Publisher	Univelt Inc.
Pages	4193-4212
Number of pages	20
ISBN (Print)	9780877036333
State	Published - 2016
Event	26th AAS/AIAA Space Flight Mechanics Meeting, 2016 - Napa, United States Duration: Feb 14 2016 → Feb 18 2016

Publication series

Name	Advances in the Astronautical Sciences
Volume	158
ISSN (Print)	0065-3438

Other

Other	26th AAS/AIAA Space Flight Mechanics Meeting, 2016
Country/Territory	United States
City	Napa
Period	2/14/16 → 2/18/16

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Resident space object shape inversion via Adaptive Hamiltonian Markov Chain Monte Carlo. / Linares, Richard; Crassidis, John L.
Spaceflight Mechanics 2016. ed. / Martin T. Ozimek; Renato Zanetti; Angela L. Bowes; Ryan P. Russell; Martin T. Ozimek. Univelt Inc., 2016. p. 4193-4212 (Advances in the Astronautical Sciences; Vol. 158).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Linares, R & Crassidis, JL 2016, Resident space object shape inversion via Adaptive Hamiltonian Markov Chain Monte Carlo. in MT Ozimek, R Zanetti, AL Bowes, RP Russell & MT Ozimek (eds), Spaceflight Mechanics 2016. Advances in the Astronautical Sciences, vol. 158, Univelt Inc., pp. 4193-4212, 26th AAS/AIAA Space Flight Mechanics Meeting, 2016, Napa, United States, 2/14/16.

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AB - This paper presents a method to determine the shape of a space object while simultaneously recovering the observed space object's inertial orientation. This paper employs an Adaptive Hamiltonian Markov Chain Monte Carlo estimation approach, which uses light curve data to infer the space object's orientation, shape, and surface parameters. This method is shown to work well for relatively high dimensions and non-Gaussian distributions of the light curve inversion problem.

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M3 - Conference contribution

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A2 - Ozimek, Martin T.

A2 - Zanetti, Renato

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T2 - 26th AAS/AIAA Space Flight Mechanics Meeting, 2016

Y2 - 14 February 2016 through 18 February 2016

ER -

Resident space object shape inversion via Adaptive Hamiltonian Markov Chain Monte Carlo

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