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dc.contributor.authorNunez, Jesse A.
dc.contributor.authorSingham, Dashi I.
dc.contributor.authorAtkinson, Michael P.
dc.date.accessioned2019-04-30T15:55:18Z
dc.date.available2019-04-30T15:55:18Z
dc.date.issued2019
dc.identifier.citationNunez, Jesse A., Dashi I. Singham, and Michael P. Atkinson. "A particle filter approach to estimating target location using Brownian bridges." Journal of the Operational Research Society (2019): 1-17.en_US
dc.identifier.urihttp://hdl.handle.net/10945/62070
dc.descriptionThe article of record as published may be found at http://dx.doi.org/10.1080/01605682.2019.1570806en_US
dc.description.abstractWe study the problem of modelling the trajectory of a moving object of interest, or target, given limited locational and temporal information. Because of uncertainty in information, the location of the target can be represented using a spatial distribution, or heatmap. This paper proposes a comprehensive method for constructing and updating probability heatmaps for the location of a moving object based on uncertain information. This method uses Brownian bridges to model and construct temporal probability heatmaps of target movement, and employs a particle filter to update the heatmap as new intelligence arrives. This approach allows for more complexity than simple deterministic motion models, and is computationally easier to implement than detailed models for local target movement.en_US
dc.description.sponsorshipCenter for Multi-Intelligence Studies at the Naval Postgraduate Schoolen_US
dc.format.extent17 p.en_US
dc.publisherTaylor and Francis Groupen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleA particle filter approach to estimating target location using Brownian bridgesen_US
dc.typeArticleen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)en_US
dc.contributor.departmentOperations Research (OR)en_US
dc.subject.authorSimulationen_US
dc.subject.authormilitaryen_US
dc.subject.authorstochastic processesen_US
dc.subject.authorBrownian bridgeen_US
dc.subject.authorparticle filteren_US


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