nahavandi-optimalmultisensor-2008.pdf (733.26 kB)
Optimal multisensor data fusion for linear systems with missing measurements
conference contribution
posted on 2008-01-01, 00:00 authored by Shady MohamedShady Mohamed, Saeid NahavandiMultisensor data fusion has attracted a lot of research in recent years. It has been widely used in many applications especially military applications for target tracking and identification. In this paper, we will handle the multisensor data fusion problem for systems suffering from the possibility of missing measurements. We present the optimal recursive fusion filter for measurements obtained from two sensors subject to random intermittent measurements. The noise covariance in the observation process is allowed to be singular which requires the use of generalized inverse. Illustration example shows the effectiveness of the proposed filter in the measurements loss case compared to the available optimal linear fusion methods.
History
Event
IEEE International Conference on System of Systems Engineering (2008 : Monterey Bay, Calif.)Pagination
1 - 4Publisher
IEEELocation
Monterey Bay, Calif.Place of publication
Piscataway, N.J.Start date
2008-06-02End date
2008-06-05ISBN-13
9781424421732Language
engNotes
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E1 Full written paper - refereedCopyright notice
2008, IEEETitle of proceedings
SOSE 2008 : IEEE International Conference on System of Systems EngineeringUsage metrics
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