The Marginalized Particle Filter in Practice
2005 (English)Report (Other academic)
The marginalized particle filter is a powerful combination of the particle filter and the Kalman filter, which can be used when the underlying model contains a linear sub-structure, subject to Gaussian noise. This paper will illustrate several positioning and target tracking applications, solved using the marginalized particle filter. Furthermore, we analyze several properties of practical importance, such as its computational complexity and how to cope with quantization effects.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2005. , 14 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2715
IdentifiersURN: urn:nbn:se:liu:diva-56044ISRN: LiTH-ISY-R-2715OAI: oai:DiVA.org:liu-56044DiVA: diva2:316897