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Optimal linear data fusion for systems with missing measurements
conference contribution
posted on 2009-01-01, 00:00 authored by Shady MohamedShady Mohamed, Saeid NahavandiIn this paper, we provide the optimal data fusion filter for linear systems suffering from possible missing measurements. The noise covariance in the observation process is allowed to be singular which requires the use of generalized inverse. The data fusion process is made on the raw data provided by two sensors observing the same entity. Each of the sensors is losing the measurements in its own data loss rate. The data fusion filter is provided in a recursive form for ease of implementation in real-world applications.
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Event
IFAC Intelligent Control Systems and Signal Processing International Conference (2nd : 2009 : Istanbul, Turkey)Pagination
1 - 4Publisher
International Federation of Automatic ControlLocation
Istanbul, TurkeyPlace of publication
Laxenburg, AustriaStart date
2009-09-21End date
2009-09-23Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2009, International Federation of Automatic ControlTitle of proceedings
ICONS 2009 : Proceedings of the IFAC Intelligent Control and Signal Processing 2009 international conferenceUsage metrics
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