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Authors: Qian Zhang and Taek Lyul Song

Affiliation: Hanyang University, Korea, Republic of

Keyword(s): Nonlinear Estimation, Very Long Range Tracking, Gaussian Mixtures, GMM-ITS.

Related Ontology Subjects/Areas/Topics: Engineering Applications ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Modeling, Analysis and Control of Discrete-event Systems ; Nonlinear Signals and Systems ; Robotics and Automation ; Sensors Fusion ; Signal Processing, Sensors, Systems Modeling and Control ; System Modeling

Abstract: Target tracking with very long range is studied in this paper. Such tracking problem has severe measurement nonlinearity that will cause consistency problems and large tracking errors. Gaussian mixture measurements are obtained by dividing the measurement likelihood into several Gaussian components. The Gaussian Mixture Measurement-Integrated Track Splitting (GMM-ITS) is applied to very long range tracking scenarios. The simulation results show that the GMM-ITS can produce consistency in the filtering results crucial to the filter performance. Furthermore, it is also able to estimate the target state accurately with small tracking errors.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Zhang, Q. and Song, T. (2015). Gaussian Mixture Measurements for Very Long Range Tracking. In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-122-9; ISSN 2184-2809, SciTePress, pages 457-464. DOI: 10.5220/0005509404570464

@conference{icinco15,
author={Qian Zhang. and Taek Lyul Song.},
title={Gaussian Mixture Measurements for Very Long Range Tracking},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2015},
pages={457-464},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005509404570464},
isbn={978-989-758-122-9},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Gaussian Mixture Measurements for Very Long Range Tracking
SN - 978-989-758-122-9
IS - 2184-2809
AU - Zhang, Q.
AU - Song, T.
PY - 2015
SP - 457
EP - 464
DO - 10.5220/0005509404570464
PB - SciTePress

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