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Optimal multisensor data fusion for linear systems with missing measurements

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conference contribution
posted on 2008-01-01, 00:00 authored by Shady MohamedShady Mohamed, Saeid Nahavandi
Multisensor 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 - 4

Publisher

IEEE

Location

Monterey Bay, Calif.

Place of publication

Piscataway, N.J.

Start date

2008-06-02

End date

2008-06-05

ISBN-13

9781424421732

Language

eng

Notes

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Publication classification

E1 Full written paper - refereed

Copyright notice

2008, IEEE

Title of proceedings

SOSE 2008 : IEEE International Conference on System of Systems Engineering

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