Comparison of few particle filter varieties

• Autorzy: Kozierski P. , Lis M.
• Języki publikacji: EN

Abstrakty

EN

Particle filters are very popular - number of algorithms based on Sequential Monte Carlo methods is growing. Paper describes and compares the performance of four of them: Auxiliary Particle Filter - this approach should reduce the high sensitivity to outliers values and poor posterior approximation, Rao-Blackwellised Particle Filter - this approach is recommended for objects with linear and nonlinear state variables, Bootstrap Filter - the first proposed Particle Filter which still can be used, because is very simple to implement, and some variety of SIR algorithm - this algorithm was chosen to show, that importance density also can be constant. The obtained results show that Bootstrap Filter and Rao-Blackwellised approaches give good results, but Bootstrap Filter works 10 times faster. The worst results gives SIR algorithm with unconditional importance function.

Słowa kluczowe

EN

particle filter; Auxiliary; Bootstrap; Rao-Blackwellised; Sequential Monte Carlo

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Computer Applications in Electrical Engineering
• Rocznik: 2013
• Tom: Vol. 11
• Strony: 345--355
• Opis fizyczny: Bibliogr. 19 poz., rys.

Twórcy

autor

Kozierski P.

• Poznań University of Technology, 60-965 Poznań, ul. Piotrowo 3a

autor

Lis M.

• Poznań University of Technology, 60-965 Poznań, ul. Piotrowo 3a

Bibliografia

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