Abstract
This research addresses the use of dual-polarimetric descriptors for automatic large-scale ship detection and characterization from synthetic aperture radar (SAR) data. Ship detection is usually performed independently on each polarization channel and the detection results are merged subsequently. In this study, we propose to make use of the complex coherence between the two polarization channels of Sentinel-1 and to perform vessel detection in this domain. Therefore, an automatic algorithm, based on the dual-polarization coherence, and applicable to entire large scale SAR scenes in a timely manner, is developed. Automatic identification system (AIS) data are used for an extensive and also large scale cross-comparison with the SAR-based detections. The comparative assessment allows us to evaluate the added-value of the dual-polarization complex coherence, with respect to SAR intensity images in ship detection, as well as the SAR detection performances depending on a vessel’s size. The proposed methodology is justified statistically and tested on Sentinel-1 data acquired over two different and contrasting, in terms of traffic conditions, areas: the English Channel the and Pacific coastline of Mexico. The results indicate a very high SAR detection rate, i.e., >80%, for vessels larger than 60 m and a decrease of detection rate up to 40 % for smaller size vessels. In addition, the analysis highlights many SAR detections without corresponding AIS positions, indicating the complementarity of SAR with respect to cooperative sources for detecting dark vessels.
Highlights
Nowadays, over 80% of the world’s trade is carried out by vessels navigating daily across the globe [1]
The proposed methodology has been applied to different Sentinel-1 datasets and the results have been compared with corresponding automatic identification system (AIS) positions interpolated from AIS data flows
synthetic aperture radar (SAR) detection results derived from the state-of-the-art constant false alarm rate (CFAR) algorithm applied to the separate dual polarization intensity channels, have been used in a comparative study
Summary
Over 80% of the world’s trade is carried out by vessels navigating daily across the globe [1]. The maritime traffic is threatened by piracy attacks and other illegal activities such as drug trafficking, unreported and unregulated fishing or illegal immigration In this context, maritime surveillance (MS), defined as the ability to monitor multiple sea activities, ranging from safe and secure transportation to illegal fishery, piracy or embargo breaches, permits us to create a comprehensive awareness of the maritime domain. MS is usually made possible by integrating information extracted from various data sources including space-based sensors, land-based surveillance stations or in-situ observations. This information allows us to localize and track ships at a large scale in a timely manner. Ship detection applications based on SAR data have multiplied in the last decade, their importance being supported by the commercial sector, as mentioned in [2]
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