A particle filter approach to estimating target location using Brownian bridges
Authors
Nunez, Jesse A.
Singham, Dashi I.
Atkinson, Michael P.
Subjects
Simulation
military
stochastic processes
Brownian bridge
particle filter
military
stochastic processes
Brownian bridge
particle filter
Advisors
Date of Issue
2019
Date
Publisher
Taylor and Francis Group
Language
Abstract
We 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.
Type
Article
Description
The article of record as published may be found at http://dx.doi.org/10.1080/01605682.2019.1570806
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Center for Multi-Intelligence Studies at the Naval Postgraduate School
Funder
Format
17 p.
Citation
Nunez, 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.
Distribution Statement
Rights
This 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.