@inproceedings{eede38cf7b024648986cd8fb18164447,
title = "Investigation of variable discretization resolution for CD-EKFs in space object tracking",
abstract = "Space object (satellite or space debris) tracking has been identified as a key component of Space Situational Awareness. Space object tracking is a continuous-discrete filtering problem. Conventional extended Kahnan filter (EKF) and un-scented Kalman filter (UKF) methods are formulated for discrete-discrete filtering problems. New versions of the EKF have been engineered recently for continuous-discrete filtering problems. We first discuss the dynamic and observation model of the space object tracking problem on which we later on test 5 filters in the CD-EKF framework. Our results show that for the space object tracking problem with radar, solutions which discretize the Langevin equation give results comparable to Moment-Matching based EKFs at very high discretization resolutions.",
author = "Ashiv Dhondea and Mishra, \{Amit K.\} and Mike Inggs",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Conference on Computer, Communication, and Signal Processing, ICCCSP 2017 ; Conference date: 10-01-2017 Through 11-01-2017",
year = "2017",
month = jan,
day = "10",
doi = "10.1109/ICCCSP.2017.7944067",
language = "English",
series = "International Conference on Computer, Communication, and Signal Processing: Special Focus on IoT, ICCCSP 2017",
publisher = "IEEE Press",
booktitle = "International Conference on Computer, Communication, and Signal Processing",
address = "United States of America",
}