Covariance Estimation and Gaussianity Assessment for State and Measurement Noise

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43956256" target="_blank" >RIV/49777513:23520/19:43956256 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.2514/1.G004348" target="_blank" >https://doi.org/10.2514/1.G004348</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2514/1.G004348" target="_blank" >10.2514/1.G004348</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Covariance Estimation and Gaussianity Assessment for State and Measurement Noise

Popis výsledku v původním jazyce

This paper deals with estimation and assessment of the characteristics of the noises of a system described by the linear state-space model. In particular, the emphasis on the recently introduced Noise Covariance Matrices Estimation with Gaussianity Assessment (NEGA) method demonstrates the ability to provide unbiased and consistent estimates of the state and measurement noise covariance matrices and a statistical hypothesis-test-based decision regarding the noises Gaussianity for a time-varying model. The NEGA method is briefly reviewed and theoretically extended in three directions; (i) design parameter specification, (ii) thorough analysis on selection of a statistical test for Gaussianity assessment, and (iii) design of efficient algorithm for the time-invariant models. The theoretical results are illustrated in a Monte-Carlo based numerical study using exemplary MATLAB implementations of the method.

Název v anglickém jazyce

Covariance Estimation and Gaussianity Assessment for State and Measurement Noise

Popis výsledku anglicky

This paper deals with estimation and assessment of the characteristics of the noises of a system described by the linear state-space model. In particular, the emphasis on the recently introduced Noise Covariance Matrices Estimation with Gaussianity Assessment (NEGA) method demonstrates the ability to provide unbiased and consistent estimates of the state and measurement noise covariance matrices and a statistical hypothesis-test-based decision regarding the noises Gaussianity for a time-varying model. The NEGA method is briefly reviewed and theoretically extended in three directions; (i) design parameter specification, (ii) thorough analysis on selection of a statistical test for Gaussianity assessment, and (iii) design of efficient algorithm for the time-invariant models. The theoretical results are illustrated in a Monte-Carlo based numerical study using exemplary MATLAB implementations of the method.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Journal of Guidance, Control, and Dynamics

ISSN

0731-5090

e-ISSN

—

Svazek periodika

43

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

132-139

Kód UT WoS článku

000506663500012

EID výsledku v databázi Scopus

2-s2.0-85078213283