Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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An Optimization Method for BAQ(Block Adaptive Quantization) Threshold Table Using Real SAR Raw Data

영상레이다 원시데이터를 이용한 BAQ(Block Adaptive Quantization) 최적화 방법

  • Lim, Sungjae (The 3rd Research and Development Institute, Agency for Defense Development) ;
  • Lee, Hyonik (The 3rd Research and Development Institute, Agency for Defense Development) ;
  • Kim, Seyoung (The 3rd Research and Development Institute, Agency for Defense Development) ;
  • Nam, Changho (The 3rd Research and Development Institute, Agency for Defense Development)
  • 임성재 (국방과학연구소 제3기술연구본부) ;
  • 이현익 (국방과학연구소 제3기술연구본부) ;
  • 김세영 (국방과학연구소 제3기술연구본부) ;
  • 남창호 (국방과학연구소 제3기술연구본부)
  • Received : 2016.06.27
  • Accepted : 2017.02.10
  • Published : 2017.04.05
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Abstract

The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

Keywords

References

  1. G. Dirk et al., "Sentinel 1 System," EUSAR 2014, 10th European Conference on Synthetic Aperture Radar; Proceeding of, pp. 1-3, June, 2014.
  2. J. Jurgen, G. Steffen, S. Thomas and K. Alexander, "From TerraSAR-X Towards Terrasar Next Generation," EUSAR 2014, 10th European Conference on Synthetic Aperture Radar; Proceeding of, pp. 1337-1340, June, 2014.
  3. R. Kwok and W. Johnson, "Block Adaptive Quantization of Magellan SAR Data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 27, No. 4, pp. 375-383, 1989. https://doi.org/10.1109/36.29557
  4. M. Younis, J. Boer, C. Ortega, D. Schulze, S. Huber and J. Mittermayer, "Determining the Optimum Compromise between SAR Data Compression and Radiometric Performance-An Approch based on the Analysis of TerraSAR-X Data," IGARSS 2008, IEEE International Geoscience Remote Sensing Symposium, pp. III-107-III-110, July, 2008.
  5. D. Lancashire, B. Barnes and S. Udall, U.S. Patent No. 6,255,987. Washington, DC: U.S. Patent and Trademark Office, 2001.
  6. Monet. P, and Dubois. E, "Block Adaptive Quantization of Images," IEEE Transactions on Communications, 41(2), 303-306, 1993. https://doi.org/10.1109/26.216503
  7. E. Attema, C. Cafforio, M. Gottwald, P. Guccione, A. Monti Guarnieri, F. Rocca, and P. Snoeij, "Flexible Dynamic Block Adaptive Quantization for Sentinel-1 SAR Missions," IEEE Geoscience and Remote Sensing Letters, Vol. 7, No. 4, pp. 766-770, Oct, 2010. https://doi.org/10.1109/LGRS.2010.2047242
  8. M. Martone, B. Brautigam, and G. Krieger, "Azimuth-Switched Quantization for SAR Systems and Performance Analysis on TanDEM-X Data," IEEE Geoscience and Remote Sensing Letters, Vol. 11, No. 1, pp. 181-185, Jan, 2014. https://doi.org/10.1109/LGRS.2013.2251603
  9. S. Lim, S. Shim, S. Kim and C. Nam, "Study on the Application of the Block Adaptive Quantization on High Bit Raw Data of the Synthetic Aperture Radar," KIMST Annual Conference Proceedings, Vol. 2015, No. 2, pp. 911-912, 2015.
  10. A. Gersho, "Principles of Quantization," IEEE Transactions on Circuits and Systems, Vol. CAS-25, No. 7, pp. 427-436, 1978.
  11. M. Martone, B. Brautigam and G. Krieger, "Quantization Effects in TanDEM-X Data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 53, No. 2, pp. 583-597, 2015. https://doi.org/10.1109/TGRS.2014.2325976
  12. Theo Algra, "Compression of Raw SAR Data Using Entropy-Constrained Quantization," IGARSS 2000, IEEE International Geoscience Remote Sensing Symposium, Vol. 6, pp. 2660-2662, July, 2002.
  13. S. Lloyd, "Least Squares Quantization in PCM," IEEE Transactions on Information Theory, Vol IT-28, No. 2, pp. 129-137, 1982.
  14. J. Mittermayer, M. Younis, R. Metzig, S. Wollstadt, J. M. Martinez, and A. Meta, "TerraSAR-X System Performance Characterization and Verification," IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 2, pp. 660-676, Feb, 2002. https://doi.org/10.1109/TGRS.2009.2026742
  15. P. Rizzoli, B. Brautigam, S. Wollstadt, and J. Mittermayer, "Radar Backscatter Mapping Using TerraSAR-X," IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 10, pp. 3538-3547, Oct, 2011. https://doi.org/10.1109/TGRS.2011.2161874
  16. P. Rizzoli, and B. Brautigam, "Radar Backscatter Modeling Based on Global TanDEM-X Mission Data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 52, No. 9, pp. 5974-5988, Sep, 2014. https://doi.org/10.1109/TGRS.2013.2294352