The optimal robust finite-horizon Kalman filtering for multiple sensors with different stochastic failure rates
Author:
Funder
Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Southwest University for Nationalities
Publisher
Elsevier BV
Subject
Applied Mathematics
Reference15 articles.
1. Variance-constrained H∞ filtering for a class of nonlinear time-varying systems with multiple missing measurements: the finite-horizon case;Dong;IEEE Trans. Signal Process.,2010
2. Robust minimum variance linear state estimators for multiple sensors with different failure rates;Hounkpevi;Automatica,2007
3. Kalman filtering with intermittent observations;Sinopoli;IEEE Trans. Automat. Control,2004
4. Variance-constrained filtering for uncertain stochastic systems with missing measurements;Wang;IEEE Trans. Automat. Control,2003
5. Robust finite-horizon filtering for stochastic systems with missing measurements;Wang;IEEE Signal Process. Lett.,2005
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