1212 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 47, NO. 4, APRIL 2009
Phenomenological Vessel Scattering Study
Based on Simulated Inverse SAR Imagery
Gerard Margarit, Member, IEEE, Jordi J. Mallorquí, Member, IEEE,
Joaquim Fortuny-Guasch, Senior Member, IEEE, and Carlos López-Martínez, Member, IEEE
Abstract—This paper presents a study on the origin of the
dominating scattering mechanisms observed in polarimetric syn-
thetic aperture radar (SAR) images of ships. The study has been
made by using numerical simulations, which have been carried
out with a radar cross section (RCS) prediction tool (GRaphical
Electromagnetic COmputing) and a SAR simulator. Extensive
series of simulations has been run for realistic 3-D geometrical
models of ships with various sizes. Different radar parameters,
aspect angles, and sea surface states have been considered in
the scenario. Data analysis with coherent target decompositions
has indicated characteristic polarimetric signatures for particular
ships within a specific range of viewing angles. This happens
at highly oblique incidences where the responses appear to be
less sensitive to changes in the operating frequency and bearing
angles. Under such conditions, ship scattering can be schematized
by the distribution of a set of guide scatterers with high RCS.
Their positions and polarimetric characteristics are quantitatively
summarized in a new feature vector, which has been proposed
to be the basis for classification algorithms. Key ideas about this
vector are presented at the end of this paper, jointly with some
examples related to three different ships. Recent publications have
shown that they can be successfully cast within a new unsupervised
vessel classification scheme.
Index Terms—Coherent target decompositions (CTDs), polari-
metric synthetic aperture radar (SAR) interferometry, SAR po-
larimetry, vessel identification.
I. I NTRODUCTION
I
N THE LAST years, fishery authorities worldwide have
become aware of the necessity to reach a sustainable ex-
ploitation. The increasing world population with a growing
consumption per capita is putting intense pressure on ocean
coastal areas, overconsuming ocean resources and endangering
a complex and fragile ecosystem. One of the main hot spots is
overfishing, as recent studies indicate that 80% of the world’s
fisheries are nowadays close to their maximum sustainable
Manuscript received October 19 2007; revised March 12, 2008, July 25,
2008, and September 23, 2008. Current version published March 27, 2009. This
work was supported by the Spanish MEC and EU FEDER funds under Project
TEC2005-06863-C02-01.
G. Margarit was with the Remote Sensing Laboratory, Department of Signal
Theory and Communications, Universitat Politècnica de Catalunya, 08034
Barcelona, Spain. He is now with the Science and Earth Observation Processing
Systems Unit, GMV Aerospace and Defense, 08006 Barcelona, Spain.
J. J. Mallorquí and C. López-Martínez are with the Remote Sensing
Laboratory, Department of Signal Theory and Communications, Universitat
Politècnica de Catalunya, 08034 Barcelona, Spain.
J. Fortuny-Guasch is with the Institute for the Protection and Security of the
Citizen, European Commission Joint Research Centre, 21027 Ispra, Italy.
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TGRS.2008.2008443
production [1], [2]. In this context, the enforcement of a tighter
fisheries regulation is presently under discussion.
The surveillance of the activity of fishing vessels is a very
important aspect in this regulation. Current vessel monitor-
ing techniques include active transponders [3], optical remote
sensing [4], passive acoustic sensors [5], or inverse synthetic
aperture radar (ISAR) imagery [6]. The lessons learned in real
scenarios have shown that none of these techniques, alone,
is sufficiently effective. The main limitations are the high
influence of the observation conditions and the lack of tracking
autonomy and independence. Other solutions should be then
considered, and SAR imagery seems the best option as it can
monitor large areas with up to meter resolutions.
SAR imagery has been proposed for supporting ship moni-
toring (see Improving fisheries Monitoring through integrating
Passive and Active Satellite-based Technologies [4], DEtection,
Classification and Identification of Marine traffic from Space
[7], and Land and sea Monitoring for Environment and Se-
curity [8] projects). Some studies have proven its usefulness
in ship detection (see [9]–[13] and the excellent review of
[14]); however, the studies have also shown the difficulties on
classifying vessels by means of their reflectivity properties.
Until now, most of the classification schemes are specifically
conceived for single-polarization SAR images. They are based
on features directly linked to the statistics of the radar ship sig-
nature and provide a decision by correlating the measurements
with large databases of historical reports [15], [16]. However,
despite their established use, their operational exploitation has
appeared to be limited because additional information channels
are required.
Recently, some studies have shown the improved classifica-
tion performance that may be obtained with SAR polarimetry
[17], [18]. The possibility of isolating more and different
features within the ship signature seems advantageous for
increasing the discrimination capability. However, the analy-
sis of real and simulated data has shown that the reached
improvements are still insufficient. Two main restrictions are
observed, namely: 1) The resolution of most orbital SAR mis-
sions was not high enough for vessel discrimination, and 2) the
information about the polarimetric phenomenology of vessels
is very limited, and this prevents one from knowing how to
interpret and exploit the scattering information for classifica-
tion. In the past, this misinformation has caused the extended
(but erroneous) assumption that vessel classification cannot be
significantly improved by using polarimetric SAR (due to the
supposed high sensitivity with respect to the observation condi-
tions). This issue is deeply analyzed in this paper, showing the
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