Accurate Density-Weighted Convolution for Point-Mass Filter and Predictor
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F21%3A43962469" target="_blank" >RIV/49777513:23520/21:43962469 - isvavai.cz</a>
Result on the web
<a href="https://dx.doi.org/10.1109/TAES.2021.3079568" target="_blank" >https://dx.doi.org/10.1109/TAES.2021.3079568</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TAES.2021.3079568" target="_blank" >10.1109/TAES.2021.3079568</a>
Alternative languages
Result language
angličtina
Original language name
Accurate Density-Weighted Convolution for Point-Mass Filter and Predictor
Original language description
This paper deals with the Bayesian state estimation of nonlinear stochastic dynamic systems. The stress is laid on the numerical solution to the Chapman-Kolmogorov equation, which governs the prediction step of the point-mass filter and predictor, using the convolution. A novel density-weighted convolution is proposed, which provides an accurate predictive probability density function even for models with small state noise, where the standard solution fails. Two implementations of the solution are proposed, theoretically analyzed, and evaluated in a numerical study.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Aerospace and Electronic Systems
ISSN
0018-9251
e-ISSN
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Volume of the periodical
57
Issue of the periodical within the volume
6
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
3574-3584
UT code for WoS article
000725819700005
EID of the result in the Scopus database
2-s2.0-85105868526