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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.
...
Pages: 13
Size: 1,214 kb
Paper DOI: 10.2495/SAFE090311
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