Sensor selection for passive sensor networks in dynamic environment: A dynamic data-driven approach

Yue Li, Devesh K. Jha, Asok Ray, Thomas A. Wettergren

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    This paper addresses the sensor selection problem in a passive sensor network under dynamically varying environment. It is assumed that sensors in the same local area share similar dynamic environmental characteristics but only a few may have events within their respective sensing radii. The main challenge is to select sensors for separation in two categories: (i) those sensors whose outputs contain combined information of event and dynamic environment and (ii) those sensors whose outputs contain the environment information only. The criteria for sensor selection is made based on the entropy rate measurements of the standard Probabilistic Finite State Automata (PFSA) constructed from sensor time series and cross D-Markov machines constructed from combined time series of a sensor and the first (i.e., dominant) principal component representing the dominant linear mode in the ensemble of related sensor data within the network. The proposed method is applied to experimental data collected from a small local passive sensor network for target detection under dynamic environments, where characteristics of environmental signal is similar to the target signal in the sense of time scale and texture.

    Original languageEnglish (US)
    Title of host publication2016 American Control Conference, ACC 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages4924-4929
    Number of pages6
    ISBN (Electronic)9781467386821
    DOIs
    StatePublished - Jul 28 2016
    Event2016 American Control Conference, ACC 2016 - Boston, United States
    Duration: Jul 6 2016Jul 8 2016

    Publication series

    NameProceedings of the American Control Conference
    Volume2016-July
    ISSN (Print)0743-1619

    Other

    Other2016 American Control Conference, ACC 2016
    CountryUnited States
    CityBoston
    Period7/6/167/8/16

    Fingerprint

    Sensor networks
    Sensors
    Time series
    Finite automata
    Target tracking
    Entropy
    Textures

    All Science Journal Classification (ASJC) codes

    • Electrical and Electronic Engineering

    Cite this

    Li, Y., Jha, D. K., Ray, A., & Wettergren, T. A. (2016). Sensor selection for passive sensor networks in dynamic environment: A dynamic data-driven approach. In 2016 American Control Conference, ACC 2016 (pp. 4924-4929). [7526133] (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7526133
    Li, Yue ; Jha, Devesh K. ; Ray, Asok ; Wettergren, Thomas A. / Sensor selection for passive sensor networks in dynamic environment : A dynamic data-driven approach. 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 4924-4929 (Proceedings of the American Control Conference).
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    abstract = "This paper addresses the sensor selection problem in a passive sensor network under dynamically varying environment. It is assumed that sensors in the same local area share similar dynamic environmental characteristics but only a few may have events within their respective sensing radii. The main challenge is to select sensors for separation in two categories: (i) those sensors whose outputs contain combined information of event and dynamic environment and (ii) those sensors whose outputs contain the environment information only. The criteria for sensor selection is made based on the entropy rate measurements of the standard Probabilistic Finite State Automata (PFSA) constructed from sensor time series and cross D-Markov machines constructed from combined time series of a sensor and the first (i.e., dominant) principal component representing the dominant linear mode in the ensemble of related sensor data within the network. The proposed method is applied to experimental data collected from a small local passive sensor network for target detection under dynamic environments, where characteristics of environmental signal is similar to the target signal in the sense of time scale and texture.",
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    Li, Y, Jha, DK, Ray, A & Wettergren, TA 2016, Sensor selection for passive sensor networks in dynamic environment: A dynamic data-driven approach. in 2016 American Control Conference, ACC 2016., 7526133, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 4924-4929, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7526133

    Sensor selection for passive sensor networks in dynamic environment : A dynamic data-driven approach. / Li, Yue; Jha, Devesh K.; Ray, Asok; Wettergren, Thomas A.

    2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 4924-4929 7526133 (Proceedings of the American Control Conference; Vol. 2016-July).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    Li Y, Jha DK, Ray A, Wettergren TA. Sensor selection for passive sensor networks in dynamic environment: A dynamic data-driven approach. In 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 4924-4929. 7526133. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2016.7526133