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On Estimation of Unknown Disturbances of Non-Linear State-Space Model Using Marginalized Particle Filter
- 1.0322493 - ÚTIA 2009 CZ eng V - Research Report
Šmídl, Václav
On Estimation of Unknown Disturbances of Non-Linear State-Space Model Using Marginalized Particle Filter.
[Odhad neznámé variance nelineárního stavového modelu pomocí marginalizovaného particle filteru.]
Praha: ÚTIA AV ČR, 2008. 19 s. Research Report, 2245.
R&D Projects: GA MŠMT 1M0572; GA ČR GP102/08/P250
Institutional research plan: CEZ:AV0Z10750506
Keywords : particle filter * unknown covariance matrix * Bayesian filtering
Subject RIV: BC - Control Systems Theory
http://library.utia.cas.cz/separaty/2008/AS/smidl-on estimation of unknown disturbances of non-linear state-space model using marginalized particle filter.pdf
The problem of estimation of unknown covariance matrix of non-linear state-space model is studied. The proposed methodology is based on combination of Extended Kalman Filter with particle filter. It is shown that the approach is promising for limited number of unknown parameters. More demanding problems with completely unknown covariance structures can not be reliably estimated since the observed data do not carry enough information.
Práce se zabývá odhadem neznámé kovarianční matice nelineárního stavového modelu. Navržená metodika je kombinací rozšířeného Kalmanova filtru s particle filtrem. Výsledná metoda funguje velmi dobře pro kovarianční matice s danou omezenou strukturou. Složitější problémy s plnou strukturou kovarianční matice nelze spolehlivě odhadnout díky nedostatečné informační hodnotě pozorovaných dat.
Permanent Link: http://hdl.handle.net/11104/0170734
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