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Group object structure and state estimation in the presence of measurement origin uncertainty.

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Group object structure and state estimation in the presence of measurement origin uncertainty. / Mihaylova, Lyudmila; Gning, Amadou.
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on. 2009. p. 473 - 476 .

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Mihaylova, L & Gning, A 2009, Group object structure and state estimation in the presence of measurement origin uncertainty. in Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on. pp. 473 - 476 , IEEE/SP 15th Workshop on Statistical Signal Processing, Cardiff, Wales, UK, 31/08/09. https://doi.org/10.1109/SSP.2009.5278535

APA

Mihaylova, L., & Gning, A. (2009). Group object structure and state estimation in the presence of measurement origin uncertainty. In Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on (pp. 473 - 476 ) https://doi.org/10.1109/SSP.2009.5278535

Vancouver

Mihaylova L, Gning A. Group object structure and state estimation in the presence of measurement origin uncertainty. In Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on. 2009. p. 473 - 476 doi: 10.1109/SSP.2009.5278535

Author

Mihaylova, Lyudmila ; Gning, Amadou. / Group object structure and state estimation in the presence of measurement origin uncertainty. Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on. 2009. pp. 473 - 476

Bibtex

@inproceedings{f127d666688c40d7ae1db54f1e45a00c,
title = "Group object structure and state estimation in the presence of measurement origin uncertainty.",
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 = "Evolving graphs, random graphs, group target tracking, nonlinear estimation, Monte Carlo methods, data association.",
author = "Lyudmila Mihaylova and Amadou Gning",
note = "{"}{\textcopyright}2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.{"} {"}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.{"} pp. 473-476 IEEE Catalog Number: CFP09SAP-CDR ISBN: 978-1-4244-2710-9 Library of Congress: 2008905779; IEEE/SP 15th Workshop on Statistical Signal Processing ; Conference date: 31-08-2009 Through 03-09-2009",
year = "2009",
month = sep,
day = "2",
doi = "10.1109/SSP.2009.5278535",
language = "English",
isbn = "978-1-4244-2709-3",
pages = "473 -- 476 ",
booktitle = "Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on",

}

RIS

TY - GEN

T1 - Group object structure and state estimation in the presence of measurement origin uncertainty.

AU - Mihaylova, Lyudmila

AU - Gning, Amadou

N1 - "©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE." "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." pp. 473-476 IEEE Catalog Number: CFP09SAP-CDR ISBN: 978-1-4244-2710-9 Library of Congress: 2008905779

PY - 2009/9/2

Y1 - 2009/9/2

N2 - 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.

AB - 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.

KW - Evolving graphs

KW - random graphs

KW - group target tracking

KW - nonlinear estimation

KW - Monte Carlo methods

KW - data association.

U2 - 10.1109/SSP.2009.5278535

DO - 10.1109/SSP.2009.5278535

M3 - Conference contribution/Paper

SN - 978-1-4244-2709-3

SP - 473

EP - 476

BT - Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on

T2 - IEEE/SP 15th Workshop on Statistical Signal Processing

Y2 - 31 August 2009 through 3 September 2009

ER -