Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data
In the framework of maritime surveillance, vessel detection techniques based on spaceborne synthetic aperture radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. This paper deals with this topic, presenting a novel approach that expl...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/6/1582 |
| _version_ | 1797609191173521408 |
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| author | Roberto Del Prete Maria Daniela Graziano Alfredo Renga |
| author_facet | Roberto Del Prete Maria Daniela Graziano Alfredo Renga |
| author_sort | Roberto Del Prete |
| collection | DOAJ |
| description | In the framework of maritime surveillance, vessel detection techniques based on spaceborne synthetic aperture radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. This paper deals with this topic, presenting a novel approach that exploits a cascade application of a pre-screening algorithm and a discrimination phase. Pre-screening is based on a constant false alarm rate (CFAR) detector, whereas discrimination exploits sub-look analysis (SLA). For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images, demonstrating a significant reduction of up to 40% in false alarms within highly congested scenarios, along with a notable enhancement of the receiving operating characteristic (ROC) curves. For future synergic exploitation of multiple SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM, and COSMO-SkyMed images, is comprehensive, having images gathered over the same area with a short time lag (below 15 min). Finally, the diversified processing chains and the results for each mission product and scenario are discussed. Being the first dataset of single-look complex (SLC) SAR multi-frequency data, the present work intends to encourage additional investigation in this promising field of research. |
| first_indexed | 2024-03-11T05:57:06Z |
| format | Article |
| id | doaj.art-3827ae69f0ae4ff382870f6bf5bdc45b |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T05:57:06Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3827ae69f0ae4ff382870f6bf5bdc45b2023-11-17T13:39:06ZengMDPI AGRemote Sensing2072-42922023-03-01156158210.3390/rs15061582Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM DataRoberto Del Prete0Maria Daniela Graziano1Alfredo Renga2Department of Industrial Engineering, University of Naples Federico II, P.le Tecchio 80, 80125 Naples, ItalyDepartment of Industrial Engineering, University of Naples Federico II, P.le Tecchio 80, 80125 Naples, ItalyDepartment of Industrial Engineering, University of Naples Federico II, P.le Tecchio 80, 80125 Naples, ItalyIn the framework of maritime surveillance, vessel detection techniques based on spaceborne synthetic aperture radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. This paper deals with this topic, presenting a novel approach that exploits a cascade application of a pre-screening algorithm and a discrimination phase. Pre-screening is based on a constant false alarm rate (CFAR) detector, whereas discrimination exploits sub-look analysis (SLA). For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images, demonstrating a significant reduction of up to 40% in false alarms within highly congested scenarios, along with a notable enhancement of the receiving operating characteristic (ROC) curves. For future synergic exploitation of multiple SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM, and COSMO-SkyMed images, is comprehensive, having images gathered over the same area with a short time lag (below 15 min). Finally, the diversified processing chains and the results for each mission product and scenario are discussed. Being the first dataset of single-look complex (SLC) SAR multi-frequency data, the present work intends to encourage additional investigation in this promising field of research.https://www.mdpi.com/2072-4292/15/6/1582syntheticaperture radarmaritime monitoringmulti-frequencymulti-missionship detectionCFAR |
| spellingShingle | Roberto Del Prete Maria Daniela Graziano Alfredo Renga Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data Remote Sensing syntheticaperture radar maritime monitoring multi-frequency multi-mission ship detection CFAR |
| title | Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data |
| title_full | Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data |
| title_fullStr | Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data |
| title_full_unstemmed | Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data |
| title_short | Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data |
| title_sort | unified framework for ship detection in multi frequency sar images a demonstration with cosmo skymed sentinel 1 and saocom data |
| topic | syntheticaperture radar maritime monitoring multi-frequency multi-mission ship detection CFAR |
| url | https://www.mdpi.com/2072-4292/15/6/1582 |
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