Improved diagonal interacting multiple model algorithm for manoeuvering target tracking based on H∞ filter

This study is devoted to the problem of state estimate of discrete-time stochastic systems with Markov jump parameters. A robust algorithm – diagonal interacting multiple model algorithm based on H∞ filtering is presented for manoeuvering target tracking when noise of measurement is of unknown stati...

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Published in:IET control theory & applications 2015-08, Vol.9 (12), p.1887-1892
Main Authors: Fu, Xiaoyan, Shang, Yuanyuan, Yuan, Huimei
Format: Article
Language:English
Subjects:
Brief Papers
discrete time systems
discrete‐time stochastic systems
extensive Monte Carlo simulations
H∞ filter
H∞ filters
improved diagonal interacting multiple model algorithm
manoeuvering target tracking
Markov jump parameters
Monte Carlo methods
stochastic systems
target tracking
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description This study is devoted to the problem of state estimate of discrete-time stochastic systems with Markov jump parameters. A robust algorithm – diagonal interacting multiple model algorithm based on H∞ filtering is presented for manoeuvering target tracking when noise of measurement is of unknown statistics. Extensive Monte Carlo simulations show the effectiveness and superiority of the proposed algorithm.
doi_str_mv 10.1049/iet-cta.2014.0685
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source Wiley Open Access Journals
subjects Brief Papers
discrete time systems
discrete‐time stochastic systems
extensive Monte Carlo simulations
H∞ filter
H∞ filters
improved diagonal interacting multiple model algorithm
manoeuvering target tracking
Markov jump parameters
Monte Carlo methods
stochastic systems
target tracking
title Improved diagonal interacting multiple model algorithm for manoeuvering target tracking based on H∞ filter
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