DocumentCode :
1655367
Title :
Group object structure and state estimation in the presence of measurement origin uncertainty
Author :
Mihaylova, Lyudmila ; Gning, Amadou
Author_Institution :
Dept. of Commun. Syst., Lancaster Univ., Lancaster, UK
fYear :
2009
Firstpage :
473
Lastpage :
476
Abstract :
This paper proposes a technique for motion and group structure estimation of moving targets based on evolving graph networks in the presence of measurement origin uncertainty. The proposed method, through an evolving graph model, allows to jointly estimate the group target and the group structure with the uncertainty. The performance of the algorithm is evaluated and results with real ground moving target indicator data are presented.
Keywords :
graph theory; state estimation; evolving graph networks; graph model; group object structure; group structure estimation; measurement origin uncertainty; state estimation; Intelligent networks; Land vehicles; Measurement uncertainty; Motion estimation; Motion measurement; Roads; Robot sensing systems; State estimation; Surveillance; Target tracking; Evolving graphs; Monte Carlo methods; data association; group target tracking; nonlinear estimation; random graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
Conference_Location :
Cardiff
Print_ISBN :
978-1-4244-2709-3
Electronic_ISBN :
978-1-4244-2711-6
Type :
conf
DOI :
10.1109/SSP.2009.5278535
Filename :
5278535
Link To Document :
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