Maritime Domain Awareness (MDA): Ship Detection and Classification by Spaceborne Synthetic Aperture Radar
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ouchi | - |
dc.contributor.author | Martin | - |
dc.contributor.author | 양찬수 | - |
dc.date.accessioned | 2020-07-15T09:53:33Z | - |
dc.date.available | 2020-07-15T09:53:33Z | - |
dc.date.created | 2020-02-11 | - |
dc.date.issued | 2018-11-09 | - |
dc.identifier.uri | https://sciwatch.kiost.ac.kr/handle/2020.kiost/22878 | - |
dc.description.abstract | In recent years, Maritime Main Awareness (MDA) has attracted much attention. One of the important issues of MDA is ship detection and classification by spaceborne synthetic aperture radar (SAR) for its all-weather and day-and-night imagingcapabilities on a global scale. Here, in this paper, we present examples of ship detection and classification using TerraSAR-X HH/VV dual-polarization data over the Tokyo Bay, Japan and Alboran Sea in Mediterranean Sea. For ship detection,comparison is made with mean image contrast among the different algorithms, including the intensities, inter-polarization coherence, entropy, and HH-VV phase difference. For ship classification, the Ship Monitoring Service (SIMONS) developed by the author (G. M. Martin) is used. Ground-truth data were collected for validation using the simultaneous AIS (Automatic Identification) data and visual observation with a video camera (only AIS data in the Alboran Sea). Although thenumbers of samples were limited, the results of 29 ships showed that the highest image contrast was obtained with coherence (0.92), followed by entropy (0.79), and phase difference (0.73), outperforming the intensity alone (about 0.25). The classification accuracy using 19 ships with AIS data was 80%. | - |
dc.description.uri | 1 | - |
dc.language | English | - |
dc.publisher | THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS | - |
dc.relation.isPartOf | ICSANE 2018 | - |
dc.title | Maritime Domain Awareness (MDA): Ship Detection and Classification by Spaceborne Synthetic Aperture Radar | - |
dc.type | Conference | - |
dc.citation.conferencePlace | CC | - |
dc.citation.endPage | 5 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | ICSANE 2018 | - |
dc.contributor.alternativeName | 양찬수 | - |
dc.identifier.bibliographicCitation | ICSANE 2018, pp.1 - 5 | - |
dc.description.journalClass | 1 | - |