Kent, J orcid.org/0000-0002-1861-8349, Bhattacharjee, S, Faber, WR et al. (1 more author) (2020) A Unified Approach to the Orbital Tracking Problem. In: 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI). IEEE International Conference on Multisensor Fusion and Integration, 14-16 Sep 2020, Karlsruhe, Germany. IEEE ISBN 978-1-7281-6423-6
Abstract
Consider an object in orbit about the earth for which a sequence of angles-only measurements is made. This paper looks in detail at a one-step update for the filtering problem. Although the problem appears very nonlinear at first sight, it can be almost reduced to the standard linear Kalman filter by a careful formulation. The key features of this formulation are (1) the use of a local or adapted basis rather than a fixed basis for three-dimensional Euclidean space and the use of structural rather than ambient coordinates to represent the state, (2) the development of a novel "normal:conditional- normal" distribution to described the propagated position of the state, and (3) the development of a novel "Observation- Centered" Kalman filter to update the state distribution.A major advantage of this unified approach is that it gives a closed form filter which is highly accurate under a wide range of conditions, including high initial uncertainty, high eccentricity and long propagation times.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Funding Information: | Funder Grant number Air Force Research Lab Munitions Directorate FA9550-19-1-7000 |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Sep 2020 14:41 |
Last Modified: | 10 Dec 2020 00:53 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/MFI49285.2020.9235258 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:166015 |