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Fusion estimation under binary sensors
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DOI：10.1016/j.automatica.2020.108861.png)
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Abstract
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Binary sensors compress the measurement information into two possible values as output and have found applications in many fields such as medical monitoring, environment monitoring and localization. This paper is concerned with the fusion estimation problem for a class of binary sensor systems with bounded noises, where the monitored physical process is described by time-varying state-space models. Since binary sensors only provide the valid information at the switching instant, a novel uncertain measurement model is proposed to characterize this feature. Then, by constructing an upper bound of fusion/estimation error at each time, convex optimization problems are established in terms of linear matrix inequalities to design stable centralized and distributed fusion estimators. An illustrative example is given to show the effectiveness of the proposed methods. (C) 2020 Elsevier Ltd. All rights reserved.
Keywords:
Fusion estimation
Binary sensors
Bounded noises
Convex optimization
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