Non-Gaussian models in particle filters

Piotr Kozierski; Talar Sadalla; Dariusz Horla

doi:10.1109/MMAR.2015.7283858

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Title

Non-Gaussian models in particle filters

Authors

Piotr Kozierski (WE) ^{[ 1 ][ P ]}
Talar Sadalla (WE) ^{[ 1 ][ D ]}
Dariusz Horla (WE) ^{[ 1 ][ P ]}

^{[ 1 ]} Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | ^{[ P ]} employee | ^{[ D ]} phd student

Year of publication

2015

Chapter type

paper

Publication language

english

Keywords

EN

particle filter
state estimation
measurement model
transition model

Abstract

EN The impact of the usage another than the Gaussian probability density functions in transition and measurement models has been verified in the article. Cases, in which wrong models have been assumed, also have been taken into account. Simulations have been performed for two different objects. Based on the obtained results, it can be said that in some cases incorrect modelling can allow the best estimation quality.

Pages (from - to)

121 - 126

DOI

10.1109/MMAR.2015.7283858

URL

https://ieeexplore.ieee.org/document/7283858

Book

20th International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, 24-27 August, 2015

Presented on

20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015, 24-27.08.2015, Miedzyzdroje, Poland

Publication indexed in

WoS (15)

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