Author(s)

G. Margarit, J. A. Barba & A. Tabasco

Abstract

This paper presents a new ship monitoring system developed at GMV Aerospace that integrates the reports provided by the Automatic Identification System (AIS) with ship-related information derived from SAR data analysis. In contrast to other proposals, SAR data is considered here to be the main input whereas AIS polls the supporting channel. The system kernel is built by the combination of three independent modules (coastline isolation, ship detection and ship classification) with two main purposes: to increase system independence and automatism. The former tries to limit the dependence on ancillary information (such as AIS), whereas the latter on human operator intervention. The three modules are integrated in a common framework developed with state-of-the-art web technologies. The result is a new concept for ship monitoring (including automatic SAR-based ship classification) that helps to better locate the error sources and reduce their dispersion. The system is able to ingest any type of SAR data for different modes and resolution, for instance ERS, ENVISAT, PALSAR, RADARSAT series or TerraSAR-X. Obviously, the performance would be strongly related with sensor features, but the system is designed to let single-polarimetric images with medium resolution provide reasonable results. This adds multi-sensor capability, which helps to reduce report refreshing time. In the paper, some examples will be processed and the main results analyzed. Preliminary tests for the ship classification module will be also presented, profiting from the ground-truth included within AIS-reports.

Keywords