Title:

OS5-2 Global sensor selection for maneuvering target tracking in clutter

Publication: ICAROB2016
Volume: 21
Pages: 361-364
ISSN: 2188-7829
DOI: 10.5954/ICAROB.2016.OS5-2
Author(s): Wenling Li, Yingmin Jia
Publication Date: January 29, 2016
Keywords: Sensor selection, Jump Markov system, Extended Kalman filter, Maneuvering target tracking, Clutter
Abstract: This paper studies the problem of sensor selection for maneuvering target tracking in the cluttered environment. By modeling the target dynamics as jump Markov linear systems, a decentralized tracking algorithm is developed by applying the extended Kalman filter and the probabilistic data association technique. A cost function that minimizes the expected filtered mean square position error is utilized and a sensor selection scheme is proposed. A numerical example is provided to illustrate the effectiveness of the proposed approach.
PDF File: https://alife-robotics.co.jp/members2016/icarob/data/papers/OS/OS5-2.pdf
Copyright: © The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
See for details: https://creativecommons.org/licenses/by-nc/4.0/

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