Abstract

This article describes an investigation of the new possibilities offered by SAR altimetry compared with conventional altimetry in the detection and characterization of non-ocean targets. We explore the capabilities of the first SAR altimeter installed on the European Space Agency satellite CryoSat-2 for the detection and characterization of ships. We propose a methodology for the detection of anomalous targets in the radar signals, based on the advantages of SAR/Doppler processing over conventional altimetry. A simple metric is proposed for the automatic detection and separation of ship targets; additional geometric considerations are introduced, to assess the compatibility between the structures detected and the actual location and characteristics of the ships observed. A test-case is presented with multiple targets that are confirmed as large vessels cruising in the proximity of a CryoSat-2 track crossing the Alboran Sea (Western Mediterranean). The presence and position of these ships at the time of satellite passage have been corroborated by the data retrieved from the Automatic Information System database. A principal motive for this research is the future altimetry missions that will provide global SAR coverage (e.g., Sentinel-3). This methodology may complement the existing tracking systems, with particular reference to the capability of compiling global statistics based on freely available data.

Highlights

  • Maritime traffic on the world’s oceans is growing as a result of increasing international trade in commodities and goods [1]

  • This paper presents for the first time a study in which Synthetic Aperture Radar (SAR) altimetry is employed with the object of identifying and geometrically characterizing ship targets

  • Radargrams obtained after unfocused SAR compression are used to detect non-ocean scatterers in the form of bright spots clustered along a few successive received waveforms; this is significantly different from conventional altimetry whereby these targets are characterized by hyperbolic features in the thermal noise region of the received signals

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Summary

Introduction

Maritime traffic on the world’s oceans is growing as a result of increasing international trade in commodities and goods [1]. This has led to demands for improved global surveillance capability in the maritime domain, in order to monitor usage of particular maritime routes, ensure adherence to international policies and decisions concerning global sea-borne trade, reduce its adverse impacts on the marine environment, and better manage the associated risks [2]. One of the main challenges to creating a global ship density map is the possibility of generating timely statistics, independently of any support from ground services.

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