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Authors: Yuan Huang ; Sa Yong Chong and Taek Lyul Song

Affiliation: Hanyang University, Korea, Republic of

ISBN: 978-989-758-263-9

Keyword(s): Track-to-track Fusion, Centralized Fusion, Multiple Detection, LM-IPDA.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Modeling, Analysis and Control of Discrete-event Systems ; Sensors Fusion ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: The multi-sensor multiple detection target tracking problem is considered in this paper. The probability of target existence is used as the track quality measure and plays an important part in the fusion paradigm. The multiple detection linear multi-target integrated probabilistic data association (MD-LM-IPDA) is utilized and extended to the multi-sensor structure. Both centralized fusion MD-LM-IPDA and distributed track-to-track fusion MD-LM-IPDA are proposed. The centralized fusion method utilizes the information from all local sensors' measurements to get the best tracking performance but suffers from the high communication load. The distributed fusion method can control the communication load by adjusting the threshold for transmitting local tracks to the fusion center. One can make a choice between these two structures based on the tracking performance requirement and the computation resources.

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Paper citation in several formats:
Huang, Y.; Chong, S. and Song, T. (2017). Track-to-track Fusion using Multiple Detection Linear Multitarget Integrated Probabilistic Data Association.In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-263-9, pages 431-439. DOI: 10.5220/0006410104310439

@conference{icinco17,
author={Yuan Huang. and Sa Yong Chong. and Taek Lyul Song.},
title={Track-to-track Fusion using Multiple Detection Linear Multitarget Integrated Probabilistic Data Association},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2017},
pages={431-439},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006410104310439},
isbn={978-989-758-263-9},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Track-to-track Fusion using Multiple Detection Linear Multitarget Integrated Probabilistic Data Association
SN - 978-989-758-263-9
AU - Huang, Y.
AU - Chong, S.
AU - Song, T.
PY - 2017
SP - 431
EP - 439
DO - 10.5220/0006410104310439

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