Design of Efficient Point-Mass Filter with Terrain Aided Navigation Illustration

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43969674" target="_blank" >RIV/49777513:23520/23:43969674 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.23919/FUSION52260.2023.10224172" target="_blank" >https://doi.org/10.23919/FUSION52260.2023.10224172</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/FUSION52260.2023.10224172" target="_blank" >10.23919/FUSION52260.2023.10224172</a>

Result language
angličtina
Original language name
Design of Efficient Point-Mass Filter with Terrain Aided Navigation Illustration
Original language description
This paper deals with state estimation of stochastic models with linear state dynamics, continuous or discrete in time. The emphasis is laid on a numerical solution to the state prediction by the time-update step of the grid-point-based point-mass filter (PMF), which is the most computationally demanding part of the PMF algorithm. A novel efficient PMF (ePMF) estimator, unifying continuous and discrete, approaches is proposed, designed, and discussed. By numerical illustrations, it is shown, that the proposed ePMF can lead to a time complexity reduction that exceeds 99.9% without compromising accuracy. The MATLAB® code of the ePMF is released with this paper.
Czech name
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Czech description
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Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 2023 26th International Conference on Information Fusion, FUSION 2023
ISBN
979-8-89034-485-4
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
IEEE
Place of publication
Charleston, SC, USA
Event location
Charleston, SC, USA
Event date
Jun 27, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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