Identification of Unclassified Ships Implementing AIS Information and SAR Image-Based Ship Detection Results

Abstract

Monitoring and detecting ships via machine learning based algorithm were regarded efficient in martial and economic manners. As an algorithm regarding automated training data retrieval from SAR image was proposed, the identification of unclassified ships without AIS information could be raised as another challenging issue of ship surveillance. This study presented the effective identification algorithm of discerning unclassified ships from AIS information and the results of conventional ship detection based on machine learning. The accurately detected ships were selected from the conventional ship detection results, followed by the preprocessing of AIS information corresponding to the SAR images containing the detection results. Superposition of AIS information on accurate detection results was conducted and concluded the ships without AIS information as unclassified ships. From 3 Sentinel-1 SAR images, it obtained the average rate of identification as 85.67%. Additional research implementing the identification algorithm accompanied by rapidly acquired satellite or airborne SAR images could be effective in rendering a ship surveillance system with rapid response.