Improved Calibration of Numerical Integration Error in Sigma-Point Filters

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F21%3A43960635" target="_blank" >RIV/49777513:23520/21:43960635 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9084238" target="_blank" >https://ieeexplore.ieee.org/document/9084238</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TAC.2020.2991698" target="_blank" >10.1109/TAC.2020.2991698</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Improved Calibration of Numerical Integration Error in Sigma-Point Filters

Popis výsledku v původním jazyce

The sigma-point filters, such as the UKF, are popular alternatives to the ubiquitous EKF. The classical quadrature rules used in the sigma-point filters are motivated via polynomial approximation of the integrand, however in the applied context these assumptions cannot always be justified. As a result, quadrature error can introduce bias into estimated moments, for which there is no compensatory mechanism in the classical sigma-point filters. This can lead in turn to estimates and predictions that are poorly calibrated. In this article, we investigate the Bayes--Sard quadrature method in the context of sigma-point filters, which enables uncertainty due to quadrature error to be formalised within a probabilistic model. Our first contribution is to derive the well-known classical quadratures as special cases of the Bayes--Sard quadrature method. Based on this, a general-purpose moment transform is developed and utilised in the design of novel sigma-point filter, which explicitly accounts for the additional uncertainty due to quadrature error.

Název v anglickém jazyce

Improved Calibration of Numerical Integration Error in Sigma-Point Filters

Popis výsledku anglicky

The sigma-point filters, such as the UKF, are popular alternatives to the ubiquitous EKF. The classical quadrature rules used in the sigma-point filters are motivated via polynomial approximation of the integrand, however in the applied context these assumptions cannot always be justified. As a result, quadrature error can introduce bias into estimated moments, for which there is no compensatory mechanism in the classical sigma-point filters. This can lead in turn to estimates and predictions that are poorly calibrated. In this article, we investigate the Bayes--Sard quadrature method in the context of sigma-point filters, which enables uncertainty due to quadrature error to be formalised within a probabilistic model. Our first contribution is to derive the well-known classical quadratures as special cases of the Bayes--Sard quadrature method. Based on this, a general-purpose moment transform is developed and utilised in the design of novel sigma-point filter, which explicitly accounts for the additional uncertainty due to quadrature error.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

IEEE Transactions on Automatic Control

ISSN

0018-9286

e-ISSN

—

Svazek periodika

66

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

7

Strana od-do

1286-1292

Kód UT WoS článku

000623420100029

EID výsledku v databázi Scopus

2-s2.0-85101821054