You are not logged in.
Openly accessible

Optimal linear data fusion for systems with missing measurements

Mohamed, Shady M.K. and Nahavandi, Saeid 2009, Optimal linear data fusion for systems with missing measurements, in ICONS 2009 : Proceedings of the IFAC Intelligent Control and Signal Processing 2009 international conference, International Federation of Automatic Control, Laxenburg, Austria, pp. 1-4.

Attached Files
Name Description MIMEType Size Downloads
mohamed-optimallinear-2009.pdf Published version application/pdf 272.12KB 38

Title Optimal linear data fusion for systems with missing measurements
Author(s) Mohamed, Shady M.K.ORCID iD for Mohamed, Shady M.K. orcid.org/0000-0002-8851-1635
Nahavandi, Saeid
Conference name IFAC Intelligent Control Systems and Signal Processing International Conference (2nd : 2009 : Istanbul, Turkey)
Conference location Istanbul, Turkey
Conference dates 21 - 23 Sep. 2009
Title of proceedings ICONS 2009 : Proceedings of the IFAC Intelligent Control and Signal Processing 2009 international conference
Editor(s) [Unknown]
Publication date 2009
Conference series Intelligent Control and Signal Processing International Conference
Start page 1
End page 4
Total pages 4
Publisher International Federation of Automatic Control
Place of publication Laxenburg, Austria
Keyword(s) data fusion
kalman filter
generalised inverse.
Summary In 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.
Language eng
Field of Research 090699 Electrical and Electronic Engineering not elsewhere classified
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2009, International Federation of Automatic Control
Persistent URL http://hdl.handle.net/10536/DRO/DU:30025589

Document type: Conference Paper
Collections: Centre for Intelligent Systems Research
Open Access Collection
Connect to link resolver
 
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
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 629 Abstract Views, 60 File Downloads  -  Detailed Statistics
Created: Thu, 25 Mar 2010, 13:06:04 EST by Shady Mohamed

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.