Optimal multisensor data fusion for linear systems with missing measurements Mohamed, Shady M. and Nahavandi, Saeid 2008, Optimal multisensor data fusion for linear systems with missing measurements, in SOSE 2008 : IEEE International Conference on System of Systems Engineering, IEEE, Piscataway, N.J., pp. 1-4. Attached Files Name Description MIMEType Size Downloads nahavandi-optimalmultisensor-2008.pdf Published version application/pdf 733.26KB 309 Title Optimal multisensor data fusion for linear systems with missing measurements Author(s) Mohamed, Shady M. orcid.org/0000-0002-8851-1635 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name IEEE International Conference on System of Systems Engineering (2008 : Monterey Bay, Calif.) Conference location Monterey Bay, Calif. Conference dates 2-5 June 2008 Title of proceedings SOSE 2008 : IEEE International Conference on System of Systems Engineering Editor(s) [Unknown] Publication date 2008 Conference series International Conference on System of Systems Engineering Start page 1 End page 4 Total pages 4 Publisher IEEE Place of publication Piscataway, N.J. Summary 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. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. ISBN 9781424421732 Language eng Field of Research 090609 Signal Processing HERDC Research category E1 Full written paper - refereed Copyright notice ©2008, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30018194 Document type: Conference Paper Collections: School of Engineering and Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Fri, 14 Aug 2009, 14:05:52 EST Wed, 09 Dec 2009, 08:04:19 EST Wed, 09 Dec 2009, 08:18:37 EST Mon, 30 Aug 2010, 17:33:35 EST Tue, 07 Sep 2010, 16:05:40 EST Fri, 16 Mar 2012, 17:03:46 EST Wed, 21 Oct 2015, 13:34:15 EST Wed, 21 Oct 2015, 16:51:55 EST Tue, 06 Sep 2016, 12:55:42 EST Tue, 05 Dec 2017, 06:32:05 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 689 Abstract Views, 325 File Downloads  -  Detailed Statistics Created: Fri, 14 Aug 2009, 14:05:52 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.