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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/25192

Title: State dependent multiple model-based particle filtering for ballistic missile tracking in a low-observable environment
Authors: Yu, Miao
Chen, Wen-Hua
Chambers, Jonathan
Keywords: Multiple model
State dependent
Random nite set
Miss detection
False alarm
Particle filter
Issue Date: 2017
Publisher: © Elsevier
Citation: 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.144-154
Abstract: This 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.
Description: This paper is closed access until 30th March 2018.
Sponsor: 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.
Version: Published
DOI: 10.1016/j.ast.2017.03.028
URI: https://dspace.lboro.ac.uk/2134/25192
Publisher Link: http://dx.doi.org/10.1016/j.ast.2017.03.028
ISSN: 1270-9638
Appears in Collections:Closed Access (Aeronautical and Automotive Engineering)

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