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    Multi-Bernoulli filter based sensor selection with limited sensing range for multi-target tracking

    240009.pdf (224.5Kb)
    Access Status
    Open access
    Authors
    Kim, Du Yong
    Ma, L.
    Jeon, M.
    Date
    2015
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Kim, D.Y. and Ma, L. and Jeon, M. 2015. Multi-Bernoulli filter based sensor selection with limited sensing range for multi-target tracking, in Proceedings of the International Conference on Control, Automation and Information Sciences (ICCAIS), Oct 29-31 2015, pp. 74-79. Changshu, China: IEEE.
    Source Title
    ICCAIS 2015 - 4th International Conference on Control, Automation and Information Sciences
    DOI
    10.1109/ICCAIS.2015.7338729
    ISBN
    9781479998920
    School
    Department of Electrical and Computer Engineering
    Remarks

    © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/14146
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, we consider a sensor network with limited sensing range and present a sensor selection algorithm for multi-target tracking problem. The proposed algorithm is based on the multi-Bernoulli filtering and a collection of sub-selection problems for individual target. A sub-selection problem for each target is investigated under the framework of partially observed Markov decision process. Each sub-selection problem is solved using a combination of information theoretic method and limited sensing range. Numerical studies validate the effectiveness of our method for multi-target tracking scenario in a sensor network.

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