Multiple model ballistic missile tracking with state-dependent transitions and Gaussian particle filtering

Yu, Miao and Gong, Liyun and Oh, Hyondong and Chen, Wen-Hua and Chambers, Jonathon (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. ISSN 0018-9251

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Abstract

This 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.

Keywords:Ballistic missile tracking, multiple state models, state-dependent transition probabilities, Bayesian inference, Gaussian particle filter
Subjects:G Mathematical and Computer Sciences > G310 Applied Statistics
G Mathematical and Computer Sciences > G340 Statistical Modelling
Divisions:College of Science > School of Computer Science
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ID Code:29438
Deposited On:13 Nov 2017 10:50

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