A Particle Filter Approach to Estimating Target Location Using Brownian Bridges
Nunez, Jesse A.
Singham, Dashi I.
Atkinson, Michael P.
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Methods for determining the optimal allocation of search resources often rely on a model for target motion. Because of uncertainty in intelligence 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 distributions for the location of a moving target based on intelligence information. We develop an analytical and simulated Brownian bridge model to construct temporal probability heatmaps of target movement, and employ a particle filter to update the heatmap as new intelligence arrives. This approach allows for more complexity than simple deterministic models, and is computationally easier to implement than detailed models for local target movement.
The article of record as published may be found at https://doi.org/10.1080/01605682.2019.1570806
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.
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