The InflateSAR Campaign: Evaluating SAR Identification Capabilities of Distressed Refugee Boats

Most of the recent research in the field of marine target detection has been concentrating on ships with large metallic parts. The focus of this work is on much more challenging targets represented by small rubber inflatables. They are of importance, since in recent years they have largely been used by migrants to cross the Mediterranean Sea between Libya and Europe. The motivation of this research is to mitigate the ongoing humanitarian crisis at Europe’s southern borders. These boats, packed with up to 200 people, are in no way suitable to cross the Mediterranean Sea or any other big water body and are in distress from the moment of departure. The establishment of a satellite-based surveillance infrastructure could considerably support search and rescue missions in the Mediterranean Sea, reduce the number of such boats being missed and mitigate the ongoing death in the open ocean. In this work we describe and analyze data from the InflateSAR acquisition campaign, wherein we gathered multiple-platform SAR imagery of an original refugee inflatable. The test site for this campaign is a lake which provides background clutter that is more predictable. The analysis considered a sum of experiments, enabling investigations of a broad range of scene settings, such as the vessel’s orientation, superstructures and speed. We assess their impact on the detectability of the chosen target under different sensor parameters, such as polarimetry, resolution and incidence angle. Results show that TerraSAR-X Spotlight and Stripmap modes offer good capabilities to potentially detect those types of boats in distress. Low incidence angles and cross-polarization decrease the chance of a successful identification, whereas a fully occupied inflatable, orthogonally oriented to the line of sight, seems to be better visible than an empty one. The polarimetric analyses prove the vessel’s different polarimetric behavior in comparison with the water surface, especially when it comes to entropy. The analysis considered state-of-the-art methodologies with single polarization and dual polarization channels. Finally, different metrics are used to discuss whether and to which extent the results are applicable to other open ocean datasets. This paper does not introduce any vessel detection or classification algorithm from SAR images. Rather, its results aim at paving the way to the design and the development of a specially tailored detection algorithm for small rubber inflatables.