Stochastic Integration Filter: Theoretical and Implementation Aspects

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43953135" target="_blank" >RIV/49777513:23520/18:43953135 - isvavai.cz</a>
Result on the web
<a href="http://https:dx.doi.org/10.23919/ICIF.2018.8455586" target="_blank" >http://https:dx.doi.org/10.23919/ICIF.2018.8455586</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/ICIF.2018.8455586" target="_blank" >10.23919/ICIF.2018.8455586</a>

Result language
angličtina
Original language name
Stochastic Integration Filter: Theoretical and Implementation Aspects
Original language description
The paper focuses on state estimation of discrete-time nonlinear stochastic dynamic systems with a special focus on the stochastic integration filter. The filter is an representative of the Gaussian filter and computes the state and measurement predictive moments by making use of a stochastic integration rule. As a result, the calculated values of the moments are random variables and exhibit favorable asymptotic properties. The paper analyzes theoretical consequences of using stochastic integration rules and proposes several modifications that improve the performance of the stochastic integration filter. As the filter requires multiple iterations of the stochastic rule, its computational costs are higher in comparison with other Gaussian filters. To reduce the costs, several modifications are proposed in the paper, which are also concerned with numerical stability issues. The proposed modifications are illustrated using both static and dynamic numerical examples used in target tracking.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 21st International Conference on Information Fusion (FUSION 2018)
ISBN
978-0-9964527-6-2
ISSN
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e-ISSN
neuvedeno
Number of pages
8
Pages from-to
1699-1706
Publisher name
IEEE
Place of publication
Cambridge, UK
Event location
Cambridge, UK
Event date
Jul 10, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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