Adaptive algorithms for target tracking.

Type : Article de conférence
Auteur(s) :  L.DRIS, D.BERKANI, R.Drai, a.benammar
Année :  2015
Domaine : Electronique
Conférence: The Internationale Conference on Telecommunications and ICT (ICTTELECOM 2015)
Résumé en PDF :  (résumé en pdf)
Fulltext en PDF :  (.pdf)
Mots clés :  stochastic filtring, Kalman filter, Extended Kalman Filter, Monte Carlo Method, Particle filtre, Target tracking

Résumé : 

The quality of the tracking is greatly enhanced by arobust motion estimation.The objective is to develop a target tracking algorithm of amoving object, especially motion estimation of these. To realizethe estimate, we chose stochastic filtering techniques. He concernthe Kalman filter in the linear Gaussian, and sequential MonteCarlo methods in the nonlinear.Representation of state is permanently adapted according oncurrent observations, to best represent the system dynamics. Acomparison of the results given by the extended Kalman filterand particle filter is realized into simulation of the nonlinearsystems target tracking.