Filtering meteoroid flights using multiple unscented Kalman filters
© 2016. The American Astronomical Society. All rights reserved.Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Institute of Physics Publishing
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/16505 |
| _version_ | 1848749195907825664 |
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| author | Sansom, E. Bland, Phil Rutten, M. Paxman, J. Towner, M. |
| author_facet | Sansom, E. Bland, Phil Rutten, M. Paxman, J. Towner, M. |
| author_sort | Sansom, E. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2016. The American Astronomical Society. All rights reserved.Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries. |
| first_indexed | 2025-11-14T07:17:05Z |
| format | Journal Article |
| id | curtin-20.500.11937-16505 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:17:05Z |
| publishDate | 2016 |
| publisher | Institute of Physics Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-165052017-09-13T15:42:22Z Filtering meteoroid flights using multiple unscented Kalman filters Sansom, E. Bland, Phil Rutten, M. Paxman, J. Towner, M. © 2016. The American Astronomical Society. All rights reserved.Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries. 2016 Journal Article http://hdl.handle.net/20.500.11937/16505 10.3847/0004-6256/152/5/148 Institute of Physics Publishing restricted |
| spellingShingle | Sansom, E. Bland, Phil Rutten, M. Paxman, J. Towner, M. Filtering meteoroid flights using multiple unscented Kalman filters |
| title | Filtering meteoroid flights using multiple unscented Kalman filters |
| title_full | Filtering meteoroid flights using multiple unscented Kalman filters |
| title_fullStr | Filtering meteoroid flights using multiple unscented Kalman filters |
| title_full_unstemmed | Filtering meteoroid flights using multiple unscented Kalman filters |
| title_short | Filtering meteoroid flights using multiple unscented Kalman filters |
| title_sort | filtering meteoroid flights using multiple unscented kalman filters |
| url | http://hdl.handle.net/20.500.11937/16505 |