This document presents research on using dual-polarized COSMO-SkyMed SAR data to observe metallic targets at sea. It discusses how ship detection is important for maritime surveillance. Traditional tools like visual observation are now supplemented by remote sensing technologies like SAR. The authors' approach uses SAR data from the COSMO-SkyMed constellation, which provides dual-polarization measurements. By analyzing the correlation between HH and VV polarizations over time, their model aims to enhance detection of metallic targets against sea surface scattering. Experiments were conducted in the Gulf of Mexico and Strait of Singapore to validate this approach.

1. Introduction Our approach Experiments Conclusions
DUAL-POLARIZED COSMO SKYMED SAR
DATA TO OBSERVE METALLIC TARGETS
AT SEA
F. Nunziata, M. Montuori and M. Migliaccio
Università degli Studi di Napoli Parthenope
Dipartimento per le Tecnologie
Centro Direzionale, isola C4 - 80143 Napoli
IEEE IGARSS 2011 Conference
24-29 July 2011, Vancouver, Canada

2. Introduction Our approach Experiments Conclusions
Outline
Introduction
Motivations
State of art
Our approach
The model
Experiments
April 23rd, 2010 - Gulf of Mexico
May 26th, 2010 - Strait of Singapore
Conclusions

3. Introduction Our approach Experiments Conclusions
Outline
Introduction
Motivations
State of art
Our approach
The model
Experiments
April 23rd, 2010 - Gulf of Mexico
May 26th, 2010 - Strait of Singapore
Conclusions

4. Introduction Our approach Experiments Conclusions
An important maritime surveillance task
Ship detection is a key task in the frame of maritime
surveillance.
• Traffic control.
• Fisheries.
• Oil pollution.

5. Introduction Our approach Experiments Conclusions
An important maritime surveillance task
Ship detection is a key task in the frame of maritime
surveillance.
• Traffic control.
• Fisheries.
• Oil pollution.

6. Introduction Our approach Experiments Conclusions
An important maritime surveillance task
Ship detection is a key task in the frame of maritime
surveillance.
• Traffic control.
• Fisheries.
• Oil pollution.

7. Introduction Our approach Experiments Conclusions
Traditional tools
Traditionally ship monitoring is accomplished by:

8. Introduction Our approach Experiments Conclusions
Modern tools
Nowadays, increasing interest is devoted to innovative
technologies:

9. Introduction Our approach Experiments Conclusions
Remote sensing: SAR
Synthetic Aperture Radar is the key remote sensing tool for
ship observation.
• Global coverage.
• All weather.
• Day & night.
• Fine spatial details.

10. Introduction Our approach Experiments Conclusions
SAR ship observation: main issues
SAR observation of metallic objects at sea is not an easy task:
Main technical issues
• Speckle.
• False alarms vs. Missing
targets.
• Complexity.
Main technological issues
• Revisit time.
• Spatial resolution.

11. Introduction Our approach Experiments Conclusions
Outline
Introduction
Motivations
State of art
Our approach
The model
Experiments
April 23rd, 2010 - Gulf of Mexico
May 26th, 2010 - Strait of Singapore
Conclusions

12. Introduction Our approach Experiments Conclusions
Single-pol approaches
Several single-pol approaches have been proposed:
• Image-processing techniques (brightness anomalies. . . ).
• Physically-based techniques (CFAR, GK speckle
model. . . ).
A proper threshold is needed to achieve
the best compromise between
false alarms and missing targets rate

13. Introduction Our approach Experiments Conclusions
Multi-pol approaches
The increasing number of satellite missions equipped with
polarimetric SARs pushes toward multi-polarization
approaches.

14. Introduction Our approach Experiments Conclusions
Multi-pol approaches
Few approaches have been developed to take benefit of pol
SAR data:
• Signal processing based: centralized and decentralized.
• Electromagnetically-based: Cloude-Pottier parameters,
improved Coherent Target Decomposition (CTD) method,
polarimetric GK, symmetry. . .
• Quite complex to be implemented.
• Threshold.

15. Introduction Our approach Experiments Conclusions
Our approach
Both technical and technological issues can be tackled at the
same time

16. Introduction Our approach Experiments Conclusions
Polarimetric SAR constellation
Italian Space Agency (ASI) COSMO-SkyMed is a constellation
of four satellites equipped with radar sensors of the SAR type,
operating in the X band.
Average revisit time in the worst Dual-pol data are provided in
case < 12h PingPong mode

17. Introduction Our approach Experiments Conclusions
PingPong mode
PingPong mode implements a strip acquisition by alternating a
pair of TX/RX polarization across bursts by means of an
antenna stirring
• The signal pol is alternated
between two possible ones: VV,
HH, HV and VH.
• The time offset between two
successive bursts, τB , varies,
according to the beam type,
between 0.15s and 0.25s.

18. Introduction Our approach Experiments Conclusions
Outline
Introduction
Motivations
State of art
Our approach
The model
Experiments
April 23rd, 2010 - Gulf of Mexico
May 26th, 2010 - Strait of Singapore
Conclusions

19. Introduction Our approach Experiments Conclusions
PingPong mode & sea surface scattering
PingPong mode acts like an along-track interferometer
Two cases must be distinguished:
• Sea surface scattering.
• Sea surface scattering with a metallic target.

20. Introduction Our approach Experiments Conclusions
PingPong mode & sea surface scattering
Sea surface scattering: Bragg or tilted-Bragg model

21. Introduction Our approach Experiments Conclusions
PingPong mode & sea surface scattering
Sea surface scattering: Bragg or tilted-Bragg model
• Time offset between
successive pulses (τB ):
0.15-0.25s.
• X-band scene coherence
time (τc ): 0.01s.
• τB τc :
HH-VV mostly uncorrelated
over sea surface

22. Introduction Our approach Experiments Conclusions
PingPong mode & sea surface scattering
τC versus wind speed for CSK parameters and assuming a
Pierson Moskowitz sea surface spectrum
τC is always lower that 0.035s

23. Introduction Our approach Experiments Conclusions
PingPong mode & sea surface scattering
Metallic target scattering: High random mechanism
• Offset between successive
pulses: 0.15-0.25s.
• Large X-band scene
coherence time.
HH-VV strongly correlated over
metallic targets

24. Introduction Our approach Experiments Conclusions
In a nutshell
The HH-VV correlation, r , is expected to allow enhancing the
presence of metallic targets over the sea surface.

25. Introduction Our approach Experiments Conclusions
Data set
COSMO-SkyMed full resolution SCS SAR data gathered in
PingPong mode (HH/VV) have been ordered in the frame of
Italian Space Agency (ASI) project ID 1221: “SAR Remote
Sensing for Sea Oil Spill Observation”
• Spatial resolution 15 × 15m.
• Swath ≈ 30 × 30Km.
• Incidence angle 20 − 60 degree.
• Data size 1.2Gb - 600Mb HH and 600Mb VV.
• 5 × 5 average moving window to measure HH-VV
correlation.

26. Introduction Our approach Experiments Conclusions
Data set
Details on the CSK PingPong mode data set
A very wide range of radar parameters, sea conditions and
geographic areas is covered.

27. Introduction Our approach Experiments Conclusions
Outline
Introduction
Motivations
State of art
Our approach
The model
Experiments
April 23rd, 2010 - Gulf of Mexico
May 26th, 2010 - Strait of Singapore
Conclusions

28. Introduction Our approach Experiments Conclusions
April, 23rd 2010 Gulf of Mexico
The CSK SAR data is relevant to the polluted area of Gulf of
Mexico, the dark area can be recognized in the HH-polarized
SAR data, together with few bright spots.

29. Introduction Our approach Experiments Conclusions
April, 23rd 2010 Gulf of Mexico
The HH-VV correlation, as expected, emphasizes targets with
respect to sea background.

30. Introduction Our approach Experiments Conclusions
April, 23rd 2010 Gulf of Mexico
Free sea surface HH-VV correlation follows a Lognormal
distribution. . .
. . . a CFAR threshold can be set that calls for a 10−4 Pfa .

31. Introduction Our approach Experiments Conclusions
April, 23rd 2010 Gulf of Mexico
The whole data can be processed (4sec) by the HH-VV CFAR
filter to provide a binary output

32. Introduction Our approach Experiments Conclusions
Outline
Introduction
Motivations
State of art
Our approach
The model
Experiments
April 23rd, 2010 - Gulf of Mexico
May 26th, 2010 - Strait of Singapore
Conclusions

33. Introduction Our approach Experiments Conclusions
May, 26th 2010 Strait of Singapore
An excerpt of the HH-polarized SAR data where “few” targets
are present is shown

34. Introduction Our approach Experiments Conclusions
May, 26th 2010 Strait of Singapore
The r -image is shown. All the targets have been correctly
highlighted with respect to the background sea.

35. Introduction Our approach Experiments Conclusions
May, 26th 2010 Strait of Singapore
The CFAR r -filter output is shown. . . 137 targets are in place

36. Introduction Our approach Experiments Conclusions
Overview of the CFAR filter’s performances
Remarkable performances are obtained by employing two
nested windows whose size are 100 × 100 and 5 × 5,
respectively.
Scenes Targets Detected targets False alarms Missed targets
9 305 303 1 3

37. Introduction Our approach Experiments Conclusions
Conclusions
An electromagnetically-based approach to observe ships in
PingPong mode HH/VV CSK SCS SAR data has been
developed
• The model exploits the HH/VV time offset to distinguish
targets from sea surface.
• The model has been successfully applied to observe ships
on CSK SAR data.
• A CFAR approach has been conceived to provide a binary
output.
• The filter is very computer-time effective (4s to process a
full data).
All data used in this study are COSMO-SkyMed products - c ASI -
Agenzia Spaziale Italiana - 2010. All rights reserved.