OpenSARShip 2.0: A large-volume dataset for deeper interpretation of ship targets in Sentinel-1 imagery

In the era of big data for synthetic aperture radar (SAR), multiple SAR systems have come into service, including Sentinel-1. The support of large-volume datasets is the key to the deep interpretation of ship targets in Sentinel-1 imagery. In this paper, we present OpenSARShip 2.0, the newest and upgraded version of OpenSARShip, which is dedicated to the deeper interpretation of SAR imagery for marine surveillance. Based on the higher requirements for ship target interpretation, the OpenSARShip 2.0, covering 34528 SAR ship chips with automatic identification system (AIS) information, possesses three improvements: large volume, interference labeling, and type levels, which are described in this paper. In addition, an application case involving the geometric parameter extraction is introduced to demonstrate the applicability of the large dataset.