Robust interacting multiple model algorithms based on multi-sensor fusion criteria

DOI10.1080/00207721.2015.1029566zbMath1333.93240OpenAlexW1971618360MaRDI QIDQ2795116

Wei-Dong Zhou, Meng-Meng Liu

Publication date: 18 March 2016

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2015.1029566

zbMATH Keywords

robust filteringestimation error correlationIMM algorithmmulti-sensor fusion criteria

Mathematics Subject Classification ID

Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05)

Cites Work

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• A switched IMM-extended Viterbi estimator-based algorithm for maneuvering target tracking
• Multi-sensor information fusion white noise filter weighted by scalars based on Kálmán predictor
• A novel interacting multiple model algorithm
• Multi-sensor optimal information fusion Kalman filter
• New approach to information fusion steady-state Kalman filtering
• Novel extended Viterbi-based multiple-model algorithms for state estimation of discrete-time systems with Markov jump parameters
• General model-set design methods for multiple-model approach
• Analysis of single Gaussian approximation of Gaussian mixtures in Bayesian filtering applied to mixed multiple-model estimation

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