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A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter

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

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A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter. / Petrov, Nikolay; Mihaylova, Lyudmila; Gning, Amadou et al.
Lecture Notes from Informatics. Berlin, Germany, 2011. p. 1-11 (Lecture Notes in Informatics; Vol. P192).

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

Harvard

Petrov, N, Mihaylova, L, Gning, A & Angelova, D 2011, A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter. in Lecture Notes from Informatics. Lecture Notes in Informatics, vol. P192, Berlin, Germany, pp. 1-11, INFORMATIK 2011, Berlin, Germany, 4/10/11. <http://www.user.tu-berlin.de/komm/CD/paper/100150.pdf>

APA

Petrov, N., Mihaylova, L., Gning, A., & Angelova, D. (2011). A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter. In Lecture Notes from Informatics (pp. 1-11). (Lecture Notes in Informatics; Vol. P192).. http://www.user.tu-berlin.de/komm/CD/paper/100150.pdf

Vancouver

Petrov N, Mihaylova L, Gning A, Angelova D. A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter. In Lecture Notes from Informatics. Berlin, Germany. 2011. p. 1-11. (Lecture Notes in Informatics).

Author

Petrov, Nikolay ; Mihaylova, Lyudmila ; Gning, Amadou et al. / A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter. Lecture Notes from Informatics. Berlin, Germany, 2011. pp. 1-11 (Lecture Notes in Informatics).

Bibtex

@inproceedings{1c470efbdc734c4985af1dba88c054ac,
title = "A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter",
abstract = "Extended objects are characterised with multiple measurements originated from ifferent locations of the object surface. This paper presents a novel Sequential Monte Carlo (SMC) approach for extended object tracking in the presence of clutter. The problem is formulated for general nonlinear problems. The main contribution of this work is in the derivation of the likelihood function for nonlinear measurement functions, with sets of measurements belonging to a bounded region. Simulation results are presented when the object is surrounded by a circular region. Accurate estimation results are presented both for the object kinematic state and object extent.",
keywords = "sequential Monte Carlo methods, tracking, clutter, extended objects, state and parameter estimation",
author = "Nikolay Petrov and Lyudmila Mihaylova and Amadou Gning and Donka Angelova",
year = "2011",
month = oct,
day = "1",
language = "English",
isbn = "978-3-88579-286-4",
series = "Lecture Notes in Informatics",
pages = "1--11",
booktitle = "Lecture Notes from Informatics",
note = "INFORMATIK 2011 ; Conference date: 04-10-2011 Through 10-10-2011",

}

RIS

TY - GEN

T1 - A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter

AU - Petrov, Nikolay

AU - Mihaylova, Lyudmila

AU - Gning, Amadou

AU - Angelova, Donka

PY - 2011/10/1

Y1 - 2011/10/1

N2 - Extended objects are characterised with multiple measurements originated from ifferent locations of the object surface. This paper presents a novel Sequential Monte Carlo (SMC) approach for extended object tracking in the presence of clutter. The problem is formulated for general nonlinear problems. The main contribution of this work is in the derivation of the likelihood function for nonlinear measurement functions, with sets of measurements belonging to a bounded region. Simulation results are presented when the object is surrounded by a circular region. Accurate estimation results are presented both for the object kinematic state and object extent.

AB - Extended objects are characterised with multiple measurements originated from ifferent locations of the object surface. This paper presents a novel Sequential Monte Carlo (SMC) approach for extended object tracking in the presence of clutter. The problem is formulated for general nonlinear problems. The main contribution of this work is in the derivation of the likelihood function for nonlinear measurement functions, with sets of measurements belonging to a bounded region. Simulation results are presented when the object is surrounded by a circular region. Accurate estimation results are presented both for the object kinematic state and object extent.

KW - sequential Monte Carlo methods

KW - tracking

KW - clutter

KW - extended objects

KW - state and parameter estimation

M3 - Conference contribution/Paper

SN - 978-3-88579-286-4

T3 - Lecture Notes in Informatics

SP - 1

EP - 11

BT - Lecture Notes from Informatics

CY - Berlin, Germany

T2 - INFORMATIK 2011

Y2 - 4 October 2011 through 10 October 2011

ER -