A theoretical look at information-driven sensor management criteria

E.H. Aoki, Arunabha Bagchi, Pranab K. Mandal, Y. Boers

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    23 Citations (Scopus)

    Abstract

    In sensor management, the usefulness of information theoretic measures seems to be validated by a large number of empirical studies, but theoretical justification presented until so far, both for selection of the measure and for the use of information-driven sensor management itself, still seems inconclusive, conflicting, or debatable. In this paper, we suggest that information-driven sensor management may be justified on the basis of uncertainty reduction rather than information gain. We subsequently identify that, due to well-known relationships between Shannon entropy, mutual information and Kullback-Leibler (KL) divergence, for sensor management purposes using the Kullback-Leibler (KL) divergence (a measure of information gain; thus a relative measure) is exactly the same as using the the Shannon entropy (a measure of uncertainty; an absolute measure). This is also used to demonstrate that, if uncertainty reduction is desirable, the asymmetry of the KL divergence is not relevant to the sensor management problem. Finally, we show some counterpoints to some arguments for replacing the KL divergence with the more general Rényi divergences.
    Original languageEnglish
    Title of host publicationProceedings of the 14th International Conference on Information Fusion (FUSION 2011)
    Place of PublicationUSA
    PublisherIEEE Aerospace and Electronic Systems Society
    Pages1-8
    Number of pages8
    ISBN (Print)978-1-4577-0267-9
    Publication statusPublished - 5 Jul 2011
    Event14th International Conference on Information Fusion, FUSION 2011 - Chicago, United States
    Duration: 5 Jul 20118 Jul 2011
    Conference number: 14

    Conference

    Conference14th International Conference on Information Fusion, FUSION 2011
    Abbreviated titleFUSION 2011
    CountryUnited States
    CityChicago
    Period5/07/118/07/11

    Keywords

    • METIS-286296
    • Entropy
    • Rényi divergence
    • Sensor management
    • IR-79955
    • EWI-21683
    • Kullback-Leibler divergence
    • Information theory

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