@inproceedings{b138513b14db4ce39aa57b26514a0545,
title = "Resident space object shape inversion via Adaptive Hamiltonian Markov Chain Monte Carlo",
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.",
author = "Richard Linares and Crassidis, \{John L.\}",
year = "2016",
language = "English",
isbn = "9780877036333",
series = "Advances in the Astronautical Sciences",
publisher = "Univelt Inc.",
pages = "4193--4212",
editor = "Ozimek, \{Martin T.\} and Renato Zanetti and Bowes, \{Angela L.\} and Russell, \{Ryan P.\}",
booktitle = "Spaceflight Mechanics 2016",
note = "26th AAS/AIAA Space Flight Mechanics Meeting, 2016 ; Conference date: 14-02-2016 Through 18-02-2016",
}