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Multiple model ballistic missile tracking with state-dependent transitions and Gaussian particle filtering
journal contribution
posted on 2017-10-30, 12:37 authored by Miao Yu, Liyun Gong, Hyondong Oh, Wen-Hua ChenWen-Hua Chen, Jonathon ChambersThis paper proposes a new method for tracking
the entire trajectory of a ballistic missile from launch to impact on the ground. Multiple state models are used to represent the different ballistic missile dynamics in three flight phases: boost, coast and reentry. In particular, the
transition probabilities between state models are represented in a state-dependent way by utilising domain knowledge. Based on this modelling system and radar measurements, a
state-dependent interacting multiple model approach based on Gaussian particle filtering is developed to accurately estimate information describing the ballistic missile such as the phase of flight, position, velocity and relevant missile parameters. Comprehensive numerical simulation studies show that the proposed method outperforms the traditional multiple model approaches for ballistic missile tracking.
Funding
This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Grant number EP/K014307/1 and the MOD University Defence Research Collaboration in Signal Processing
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
IEEE Transactions on Aerospace and Electronic SystemsCitation
YU, M. ...et al., 2018. Multiple model ballistic missile tracking with state-dependent transitions and Gaussian particle filtering. IEEE Transactions on Aerospace and Electronic Systems, 54(3), pp. 1066-1081.Publisher
Institute of Electrical and Electronics Engineers (IEEE)Version
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/Acceptance date
2017-10-16Publication date
2017-11-13Notes
This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/ISSN
0018-9251Publisher version
Language
- en