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Adaptive Aircraft Trajectory Prediction using Particle Filters

Author(s):

I. Lymperopoulos, J. Lygeros
Conference/Journal:

AIAA Guidance, Navigation and Control Conference and Exhibit
Abstract:

The problem of aircraft trajectory prediction is formulated as a Bayesian estimation problem. The aircraft dynamics are modeled as a stochastic non-linear hybrid system and partial information about the state of the aircraft is provided sequentially through radar measurements. Such observations incorporate information about the missing parameters of the system and the effect of the stochastic part of the dynamics on the system state. However the nonlinear, non-Gaussian nature of the model prevents the use of traditional filtering methods such as Kalman filtering, which may other- wise provide optimal solutions for linear systems with additive Gaussian noise. To confront this problem we employ sequential Monte Carlo methods (particle filters) in order to provide a numerical solution to the recursive Bayesian estimation problem.

Year:

2008
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@InProceedings { LymLyg:2008:IFA_3155,
    author={I. Lymperopoulos and J. Lygeros},
    title={{Adaptive Aircraft Trajectory Prediction using Particle
	  Filters}},
    booktitle={AIAA Guidance, Navigation and Control Conference and
	  Exhibit},
    pages={},
    year={2008},
    address={},
    month=aug,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3155}
}
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