Lagrangian Grid-Based Filters With Application to Terrain-Aided Navigation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F25%3A43976497" target="_blank" >RIV/49777513:23520/25:43976497 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/MSP.2024.3489969" target="_blank" >https://doi.org/10.1109/MSP.2024.3489969</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/MSP.2024.3489969" target="_blank" >10.1109/MSP.2024.3489969</a>
Alternative languages
Result language
angličtina
Original language name
Lagrangian Grid-Based Filters With Application to Terrain-Aided Navigation
Original language description
The column focuses on the state estimation of discrete-time stochastic dynamic systems from noisy or incomplete measurements. State estimation has been a subject of considerable research interest for the last decades. It plays an important role in e.g. navigation, tracking, speech and image processing, fault detection, and optimal control. In this column, we introduce and explain the recent state-of-the-art efficient grid-based filtering techniques that were proven to rival the ubiquitous particle filters based on the Monte Carlo integration in terms of performance and computational complexity. Compared to the particle filters, the grid-based filters provide deterministic results with improved resilience against initialisation error and measurement outliers. The readers are guided through the design of the grid-based filters within the scope of terrain-aided navigation, which is a topical navigation solution due to the latest jamming and spoofing attacks on global navigation satellite systems. The presented algorithms and related codes in MATLAB and Python are made publicly available together with the real-world measured dataset.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotics and advanced industrial production</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Signal Processing Magazine
ISSN
1053-5888
e-ISSN
1558-0792
Volume of the periodical
42
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
7
Pages from-to
98-104
UT code for WoS article
001550524000010
EID of the result in the Scopus database
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