Wyszukiwarka
Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data
Abstrakt
The paper presents the seafloor characterisation based on multibeam sonar data. It relies on using the integrated model and description of three types of multibeam data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification is performed by utilisation of several statistical methods applied for analysis of a set of seafloor descriptors derived from multibeam data. In the paper, the use of Principal Component Analysis (PCA), as well as Canonical Discriminant Analysis (CDA) for reduction of the seafloor parameter space dimension is presented along with the obtained results. In addition, the use of the open source World Wind Java SDK tool for implementation of imaging and mapping of seafloor multibeam data, integrated with other elements of a scene and overlaid on rich background data, is also shown.
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Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- Licencja
-
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Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
- Opublikowano w:
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HYDROACOUSTICS
nr 15,
strony 123 - 130,
ISSN: 1642-1817 - Język:
- angielski
- Rok wydania:
- 2012
- Opis bibliograficzny:
- Łubniewski Z., Stepnowski A.: Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data// HYDROACOUSTICS. -Vol. 15., (2012), s.123-130
- Źródła finansowania:
-
- COST_FREE
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 79 razy