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Ship Recognition by Integration of SAR and AIS

Published online by Cambridge University Press:  12 March 2012

Sudhir Kumar Chaturvedi ,
Chan-Su Yang ,
Kazuo Ouchi  and
Palanisamy Shanmugam
Sudhir Kumar Chaturvedi
Affiliation:
(Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai, India)
Chan-Su Yang*
Affiliation:
(Korea Ocean Satellite Center, Korea Ocean Research & Development Institute, Gyeonggi-do, Korea)
Kazuo Ouchi
Affiliation:
(Department of Computer Science, School of Electrical and Computer Engineering, National Defence Academy, Kanagawa, Japan)
Palanisamy Shanmugam
Affiliation:
(Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai, India)
*
(E-mail: [email protected])
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Abstract

A novel design of an integrated system using Synthetic Aperture Radar (SAR) image and Automatic Identification System (AIS) data is proposed in this paper for the purpose of identifying ships at sea. TerraSAR-X® (SpotLight mode) images and AIS data collected over Incheon Port (Korea) and Tokyo Bay (Japan) were used on different dates. Four main steps for integration of SAR and AIS based ships can be identified, namely: ‘Time Matching’ to retrieve the respective Dead Reckoning (DR) position of the ships at SAR image acquisition times; ‘Position Matching’ based on a nearest neighbourhood re-sampling method with compensation of position shift; ‘Size Matching’ and ‘Speed Matching’. Under each of the matching criteria, the measurement error in each of the matching criteria was found to be less than 20% and the SAR extracted ship's hull boundaries were presented on a screen to display the system results. The results of this study will contribute to the design a Near-Real-Time (NRT) operational system for ship detection, identification, and classification by SARs in different data acquisition modes over various geographical locations at different acquisition times. This novel integrated system design will provide a most important preliminary step towards integration based on ships' hull monitoring in order to recognize ‘friend’ and ‘foe’ ship targets over a huge oceanic region and would be useful for coast guards as an early warning system.

Keywords

Ship Detection and RecognitionSARAISIntegrated System
Type
Research Article
Information
The Journal of Navigation , Volume 65 , Issue 2 , April 2012 , pp. 323 - 337
Copyright
Copyright © The Royal Institute of Navigation 2012

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References

REFERENCES

Arnesen, T. N. and Olsen, R. B. (2004). Literature Reviews on Vessel Detection. FFI-2004/02619, Norwegian Defence Research Establishment, Kijeller, Norway.Google Scholar
Automatic Identification System Manual. International Maritime Organization (IMO), United Nations.Google Scholar
Jackson, C. R. and Apel, J. R. (2004). Synthetic Aperture Radar Marine User's Manual, Chapter 1. Principles of Synthetic Aperture Radar, 1-24 NOAA, Washington. http://www.sarusersmanual.com/Google Scholar
Grasso, R., Mirra, S., Baldacci, A., Horstmann, J., Coffin, M. and Jarvis, M. (2009). Performance Assessment of a Mathematical Morphology Ship Detection Algorithm For SAR Images Through Comparison with AIS Data. 9th International Conference on Intelligent Systems Design and Applications, Italy.CrossRefGoogle Scholar
Lin, I-I., and Khoo, V. (1997). Computer Based Algorithm for Ship Detection from ERS SAR Imagery. 3rd ERS Symposium-Space at the Service of Our Environment, Florence, Italy.Google Scholar
Lehner, S., Brusch, S. and Fritz, T. (2009). Ship Surveillance by Joint Use of SAR and AIS. 1st International Conference of Space Technology, Thessaloniki, Greece.CrossRefGoogle Scholar
Margarit, G., Barba-Milanes, M. J. and Antonio, T. (2009). Operational Ship Monitoring System Based on Synthetic Aperture Radar Processing. Remote Sensing, 1, 375–392.CrossRefGoogle Scholar
Ouchi, K., Iehara, M., Morimura, K., Kumano, S. and Takami, I. (2002). Nonuniform Azimuth Image Shift Observed in the Radarsat Images of Ships in Motion. IEEE Transactions on Geoscience and Remote Sensing, 40, 2188–2195.CrossRefGoogle Scholar
Rany, R. K. (1971). Synthetic Aperture Radar and Moving Target. IEEE Transactions on Aerospace and Electronic Systems, 7, 499–505.CrossRefGoogle Scholar
Soille, P. (1999). Morphological Image Analysis-Principles and Applications, Springer-Verlag.CrossRefGoogle Scholar
Tunaley, J. K. and James, K. E. (2003). The Estimation of Ship Speed from SAR Imagery. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Toulouse, France.Google Scholar
Vachon, P. W., English, R. A. and Wolfe, J. (2007). Validation of RADARSAT-1 Vessel Signatures with AISLive Data. Canadian Journal of Remote Sensing, 33, 20–26.CrossRefGoogle Scholar
Wahl, T., Eldhuset, K. and Skole, A. (1993). Ship Traffic Monitoring Using the ERS-1 SAR. Proceedings of First ERS-1 Symposium-Space at the Service of our Environment, Cannes, France.Google Scholar