Reduction of prediction error sensitivity to parameters in Kalman filter
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00355728" target="_blank" >RIV/68407700:21230/22:00355728 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21720/22:00355728
Result on the web
<a href="https://doi.org/10.1016/j.jfranklin.2021.12.019" target="_blank" >https://doi.org/10.1016/j.jfranklin.2021.12.019</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jfranklin.2021.12.019" target="_blank" >10.1016/j.jfranklin.2021.12.019</a>
Alternative languages
Result language
angličtina
Original language name
Reduction of prediction error sensitivity to parameters in Kalman filter
Original language description
The desensitized Kalman filter is a practical and intuitive robust filtering method. However, a thorough analysis of its stability and impact of assumptions is missing. This paper expands the theory of desensitized Kalman filtering by proposing a stochastic approach to reduce estimation error sensitivity to parameters. The novel approach leads to the exact desensitized Kalman filter that does not neglect the gain sensitivity to a parameter. The suboptimal form equivalent to the original desensitized Kalman filter in a special form is proposed. The stability analysis and the definition of stability conditions are possible due to the proposed form that can be interpreted as the Kalman filter with correlated process and measurement noise with time-variant statistics. Furthermore, adaptive normalization of objectives is introduced, which improves the desensitizing performance.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
<a href="/en/project/GA18-26278S" target="_blank" >GA18-26278S: Incorporation of Prior Knowledge for Identification of Nonlinear Systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
ISSN
0016-0032
e-ISSN
1879-2693
Volume of the periodical
359
Issue of the periodical within the volume
3
Country of publishing house
GB - UNITED KINGDOM
Number of pages
24
Pages from-to
1303-1326
UT code for WoS article
000801856900010
EID of the result in the Scopus database
2-s2.0-85123007519