Bayesian Estimation of a Single Mass Concentration Within an Asteroid
| dc.contributor.advisor | Furfaro, Roberto | en |
| dc.contributor.author | Woodard, Aaron Jacob | |
| dc.creator | Woodard, Aaron Jacob | en |
| dc.date.accessioned | 2017-09-29T18:14:17Z | |
| dc.date.available | 2017-09-29T18:14:17Z | |
| dc.date.issued | 2017 | |
| dc.identifier.uri | http://hdl.handle.net/10150/625702 | |
| dc.description.abstract | Orbit determination has long relied on the use of the Kalman filter, or specifically the extended Kalman filter, as a means of accurately navigating spacecraft. With the advent of cheaper, more powerful computers more accurate techniques such as the particle filter have been utilized. These Bayesian types of filters have in more recent years found their way to other applications. Dr. Furfaro and B. Gaudet have demonstrated the ability of the particle filter to accurately estimate the angular velocity, homogenous density, and rotation angle of a non-uniformly rotating ellipsoid shaped asteroid. This paper extends that work by utilizing a particle filter to accurately estimate the angular velocity and homogenous density of an ellipsoidal asteroid while simultaneously determining the location and mass of a mass concentration modeled as a point mass embedded within the asteroid. This work shows that by taking measurements in several locations around the asteroid, the asteroid's rotation state and mass distribution can be discerned. | |
| dc.language.iso | en_US | en |
| dc.publisher | The University of Arizona. | en |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en |
| dc.subject | Asteroid | en |
| dc.subject | Bayesian Estimation | en |
| dc.subject | Gravity Field | en |
| dc.subject | Sequential Monte Carlo Filter | en |
| dc.title | Bayesian Estimation of a Single Mass Concentration Within an Asteroid | en_US |
| dc.type | text | en |
| dc.type | Electronic Thesis | en |
| thesis.degree.grantor | University of Arizona | en |
| thesis.degree.level | masters | en |
| dc.contributor.committeemember | Furfaro, Roberto | en |
| dc.contributor.committeemember | Lepore, Robert | en |
| dc.contributor.committeemember | Head, Larry | en |
| thesis.degree.discipline | Graduate College | en |
| thesis.degree.discipline | Systems Engineering | en |
| thesis.degree.name | M.S. | en |
| refterms.dateFOA | 2018-06-23T11:43:39Z | |
| html.description.abstract | Orbit determination has long relied on the use of the Kalman filter, or specifically the extended Kalman filter, as a means of accurately navigating spacecraft. With the advent of cheaper, more powerful computers more accurate techniques such as the particle filter have been utilized. These Bayesian types of filters have in more recent years found their way to other applications. Dr. Furfaro and B. Gaudet have demonstrated the ability of the particle filter to accurately estimate the angular velocity, homogenous density, and rotation angle of a non-uniformly rotating ellipsoid shaped asteroid. This paper extends that work by utilizing a particle filter to accurately estimate the angular velocity and homogenous density of an ellipsoidal asteroid while simultaneously determining the location and mass of a mass concentration modeled as a point mass embedded within the asteroid. This work shows that by taking measurements in several locations around the asteroid, the asteroid's rotation state and mass distribution can be discerned. |
