Unique Maximum Likelihood Localization of Nuclear Sources

B. D.O. Anderson, S. Dasgupta, H. E. Baidoo-Williams, M. F. Anjum, R. Mudumbai

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

    1 Citation (Scopus)

    Abstract

    In an earlier paper, [1], we have considered the Maximum Likelihood (ML) localization of a stationary nuclear source using the time of arrival of particles modeled as a Poisson process at a sensing vehicle moving with a constant velocity. In this paper we consider whether the ML location estimate characterized in [1] is unique. Using Morse theory we show that not only is the likelihood function unimodal on either side of the line the sensor moves on (note the source can only be localized uniquely if one knows on which side it resides), but that in fact it has only one critical point in each side and this critical point is the global maximum. These results strongly indicate that gradient ascent maximization will always work. We verify these results with real field data.

    Original languageEnglish
    Title of host publication2019 IEEE 58th Conference on Decision and Control, CDC 2019
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages4127-4132
    Number of pages6
    ISBN (Electronic)9781728113982
    DOIs
    Publication statusPublished - Dec 2019
    Event58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France
    Duration: 11 Dec 201913 Dec 2019

    Publication series

    NameProceedings of the IEEE Conference on Decision and Control
    Volume2019-December
    ISSN (Print)0743-1546
    ISSN (Electronic)2576-2370

    Conference

    Conference58th IEEE Conference on Decision and Control, CDC 2019
    Country/TerritoryFrance
    CityNice
    Period11/12/1913/12/19

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