WP2.1_PUB9.pdf (428.7 kB)
State dependent multiple model-based particle filtering for ballistic missile tracking in a low-observable environment
journal contribution
posted on 2017-05-31, 13:31 authored by Miao Yu, Wen-Hua ChenWen-Hua Chen, Jonathon ChambersThis paper proposes a new method for tracking the whole trajectory of a ballistic missile (BM), in a low-observable environment with ‘imperfect’ sensor measurement incorporating both miss detection and false alarms. A hybrid system with state dependent transition probabilities is proposed where multiple state models represent the ballistic missile movement during different phases; and domain knowledge is exploited to model the transition probabilities between different flight phases in a state-dependent way. The random finite set (RFS) is adopted to model radar sensor measurements which include both miss detection and false alarms. Based on the proposed hybrid modeling system and the RFS represented sensor measurements, a state dependent interacting multiple model particle filtering method integrated with a generalized measurement likelihood function is developed for the BM tracking. Comprehensive simulation studies show that the proposed method outperforms the traditional ones for the BM tracking, with more accurate estimations of flight mode probabilities, positions and velocities.
Funding
This work was supported by the UK 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
Aerospace Science and TechnologyVolume
67Pages
144 - 154Citation
YU, M., CHEN, W.-H. and CHAMBERS, J., 2017. State dependent multiple model-based particle filtering for ballistic missile tracking in a low-observable environment. Aerospace Science and Technology, 67, pp.144-154Publisher
© ElsevierVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2017-03-15Publication date
2017Notes
This paper was published in the journal Aerospace Science and Technology and the definitive published version is available at http://dx.doi.org/10.1016/j.ast.2017.03.028.ISSN
1270-9638Publisher version
Language
- en