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Author Kazimierski, Witold
Affiliation Maritime University of Szczecin, Faculty of Navigation, Chair of Geoinformatics 70-500 Szczecin, ul. Wały Chrobrego 1–2
E-mail w.kazimierski@am.szczecin.pl
ISSN printed 1733-8670
URI https://repository.pm.szczecin.pl/handle/123456789/65
Abstract Radar target tracking on a sea-going ship is a basic source of information about movement of other vessels, influencing directly safety of navigation. The research on improving of tracking methods has led to a new concept of multiple model neural filtration, which is a combination of multiple model approach with the use of artificial neural networks for the needs of estimation of movement vector. One of the key issue during designing of filter id to establish rules of interaction between elementary filters. The paper presents the most popular methods of manoeuvre detection and interaction of elementary filters in the numerical filtration. The modifications of them for the needs of neural tracking are proposed. Additionally, a concept of use of probabilistic neural network for this purpose is described. The idea was checked in the experimental research with the use of simulation. The result of the research confirmed usefulness of using PNN in multiple model filtration, showing however simultaneously the directions of future research in this. The research was financed by Polish National Centre of Science under the research project “Development of radar target tracking methods of floating targets with the use of multiple model neural filtering”
Pages 81–87
Publisher Scientific Journals of the Maritime University of Szczecin, Zeszyty Naukowe Akademii Morskiej w Szczecinie
Keywords radar target tracking
Keywords multiple model filters
Keywords manoeuvre detection
Title The analysis of methods of interaction between elementary filters in multiple model tracking filter in marine radars
Type Original scientific article
References
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ISSN on-line 2392-0378
Language English
Funding No data
Figures 3
Tables 2
Published 2012-12-10
Accepted 2012-11-06
Recieved 2012-10-02


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