Navigation and Estimation Improvement by Environmental-Driven Noise Mode Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43959779" target="_blank" >RIV/49777513:23520/20:43959779 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/PLANS46316.2020.9110200" target="_blank" >https://doi.org/10.1109/PLANS46316.2020.9110200</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/PLANS46316.2020.9110200" target="_blank" >10.1109/PLANS46316.2020.9110200</a>
Alternative languages
Result language
angličtina
Original language name
Navigation and Estimation Improvement by Environmental-Driven Noise Mode Detection
Original language description
This paper deals with the state estimation of nonlinear stochastic dynamic systems, where the measurement noise is modelled by the multimodal Gaussian sum probability density function. The multimodal density is able to sufficiently capture various environmental features and phenomena affecting sensor readings. The design particularly focuses on the environmentaldriven detector of the measurement noise mode for the terrain-aided navigation using a point-mass filter, which allows reducing the overall measurement noise variance used by the estimator and, consequently, decreasing the estimator or navigator error. Throughout the paper, the detector design and validation are illustrated with the help of a terrain-aided navigation system.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)
ISBN
978-1-72810-244-3
ISSN
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e-ISSN
2153-3598
Number of pages
8
Pages from-to
925-932
Publisher name
IEEE
Place of publication
Portland
Event location
Portland, Spojené státy americké
Event date
Apr 20, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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