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
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;
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
DOI :
10.1109/SSP.2009.5278535