Tram Localization using Soft-Constrained Iterated Kalman Filter with Optimal Step Size Control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00377489" target="_blank" >RIV/68407700:21230/24:00377489 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/MFI62651.2024.10705771" target="_blank" >http://dx.doi.org/10.1109/MFI62651.2024.10705771</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/MFI62651.2024.10705771" target="_blank" >10.1109/MFI62651.2024.10705771</a>

Result language
angličtina
Original language name
Tram Localization using Soft-Constrained Iterated Kalman Filter with Optimal Step Size Control
Original language description
The paper describes a way to incorporate soft constraints to iterated Kalman filter and its application to tram localization. The localization task is motivated by a suboptimal performance of a currently used hard-constrained localization solution and is then tackled by introducing a framework allowing to insert various constraints into the Kalman filter scheme. The filtering (data update) step of the iterated Kalman filter is interpreted as an instance of a non-linear least squares problem for which the step size in each iteration can be chosen in the optimal manner, improving the overall state estimate convergence. The described estimation framework is showcased on real-life data and compared against a hardconstrained Kalman filter scheme which resembles the one originally motivating the task. While the presented solution does not provide a substantial quantifiable improvement in quality of estimate in this particular case, it is much more versatile and does not require prior specific choice of tramway tracks. Finally, the introduced scheme is employed on the motivating example with a discussion of possible further enhancements.
Czech name
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Czech description
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Project
<a href="/en/project/CK03000269" target="_blank" >CK03000269: Advanced methods for on-board data processing in V2X systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
ISBN
979-8-3503-6803-1
ISSN
2835-947X
e-ISSN
2767-9357
Number of pages
6
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
Plzeň
Event date
Sep 4, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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