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Robust state estimation for jump Markov linear systems with missing measurements. (English) Zbl 1293.93717
Summary: This paper is concerned with the robust state estimation problem for a class of jump Markov linear systems (JMLSs) with missing measurements. Two independent Markov chains are used to describe the behavior of the system dynamics and the characteristic of missing measurements, respectively. A robust filtering algorithm is developed by applying the basic Interacting Multiple Model (IMM) approach and the \(H_\infty\) technique, which is different from the traditional Kalman filtering with minimum estimation error variance criterion. A maneuvering target tracking example is provided to demonstrate the effectiveness of the proposed algorithm.

MSC:
93E10 Estimation and detection in stochastic control theory
93E11 Filtering in stochastic control theory
60J75 Jump processes (MSC2010)
93C05 Linear systems in control theory
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