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Research Centre
Data - Algorithms - Decision Making
Data - Algorithms - Decision Making
Established in 2005 under support of MŠMT ČR (project 1M0572)
Publications
On Estimation of Unknown Disturbances of Non-Linear State-Space Model Using Marginalized Particle Filter
Typ:
Research report
Authors:
Name of edition:
Research Report
Article number:
2245
Publisher:
ÚTIA AV ČR
Serie:
Praha
Year:
2008
Keywords:
particle filter, unknown covariance matrix, Bayesian filteri
Anotation:
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.