Particle filtering methods for incorporating intelligence updates
Nunez, Jesse A.
Singham, Dashi I.
Atkinson, Michael P.
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Due to uncertainty in target locations, stochastic models are implemented to provide a representation of location distribution. The reliability of these models has a profound effect on the ability to successfully interdict these targets. A key factor in the reliability of a model is the incorporation of information updates. A common method for incorporating information updates is Kalman filtering. However, given the probable nonlinear and non-Gaussian nature of target movement models, the fidelity of solutions provided by Kalman filtering could be significantly degraded. A more robust methodology needs to be employed. This thesis uses an updating algorithm known as particle filtering to incorporate information updates concerning the target's position. Particle filtering is a nonparametric filtering technique that is adaptable and flexible. The particle filter is incorporated into a model that uses a stochastic process known as a Brownian bridge to model target movement. A Brownian bridge models target movement with minimal information and allows for uncertainty during periods when target location is unknown. As new intelligence arrives, the particle filter is used to update a probabilistic heat map of target position. The main goal of this thesis is to design a stochastic model integrating both the Brownian bridge model and particle filtering.
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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Nunez, Jesse A.; Singham, Dashi I.; Atkinson, Michael P. (Taylor and Francis Group, 2019);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 ...
Nunez, Jesse A.; Singham, Dashi I.; Atkinson, Michael P. (Naval Postgraduate School, 2019);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 ...
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