Importance Gauss-Hermite Gaussian Filter for Models with Non-Additive Non-Gaussian Noises

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F21%3A43962474" target="_blank" >RIV/49777513:23520/21:43962474 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9626832" target="_blank" >https://ieeexplore.ieee.org/document/9626832</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Importance Gauss-Hermite Gaussian Filter for Models with Non-Additive Non-Gaussian Noises

Popis výsledku v původním jazyce

The paper deals with the state estimation of nonlinear stochastic systems with non-additive non-Gaussian noises. A new algorithm is proposed based on the computationally efficient Gaussian filter. The non-additivity and non-Gaussianity of the noises prevents the usage of standard quadratures to evaluate the moment integrals present in the Gaussian filter as these are not Gauss-weighted. The proposed algorithm leverages the importance Gauss-Hermite method to evaluate the integrals by means of the Gaussian proposal PDF. In order to improve the evaluation quality, an iterative improvement of the proposal PDF is employed. The paper also discusses the algorithm for special cases of the model with either process or measurement noise being additive yet non-Gaussian. The performance of the proposed algorithm is illustrated using a numerical example.

Název v anglickém jazyce

Importance Gauss-Hermite Gaussian Filter for Models with Non-Additive Non-Gaussian Noises

Popis výsledku anglicky

The paper deals with the state estimation of nonlinear stochastic systems with non-additive non-Gaussian noises. A new algorithm is proposed based on the computationally efficient Gaussian filter. The non-additivity and non-Gaussianity of the noises prevents the usage of standard quadratures to evaluate the moment integrals present in the Gaussian filter as these are not Gauss-weighted. The proposed algorithm leverages the importance Gauss-Hermite method to evaluate the integrals by means of the Gaussian proposal PDF. In order to improve the evaluation quality, an iterative improvement of the proposal PDF is employed. The paper also discusses the algorithm for special cases of the model with either process or measurement noise being additive yet non-Gaussian. The performance of the proposed algorithm is illustrated using a numerical example.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GC20-06054J" target="_blank" >GC20-06054J: Inteligentní distribuované architektury pro odhad stavu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2021 IEEE 24th International Conference on Information Fusion (FUSION)

ISBN

978-1-73774-971-4

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

1-7

Název nakladatele

IEEE

Místo vydání

Sun City

Místo konání akce

Sun City, Jihoafrická republika

Datum konání akce

1. 11. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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