| 摘要(英) |
The resolution requirements of remote sensing images become higher and the channel capacity from satellites to the ground stations is limited. In order to effectively reduce the image data of synthetic aperture radar and maintain good image resolution, a block adaptive quantizer (BAQ) is needed to compress the echo signals. In the BAQ, the input signals of the in-phase (I) and quadrature (Q) axes are divided into blocks. The statistics of each block such as the average energy is calculated to derive the parameters of Lloyd-Max quantizer including the thresholds and the representatives of each quantized region. The Lloyd-Max quantizer achieves the smallest mean square error (MSE) of the Gaussian distributed signals. The signal-to-noise ratio (SNR) based on the average energy of the input signals and the MSE of the quantized output is then evaluated. In our BAQ system, it can compress the ADC signals of 8,10,12,14 bits into 2, 3, 4, 6 or 8 bits outputs. The block size can be set as 128, 256 or 512 complex samples, and the whole possible variance range can be divided equally into either 128 or 256 segments depending on the user requirements.
When the BAQ output wordlength is large, the memory for storing the Lloyd-Max quantizer thresholds is huge. Thus, we propose to use variance scaling technique to normalize the input signal energy. In this case, only one set of thresholds is needed with an extra memory for storage of variance scaling values. Over 98% memory sizes can be saved. In order to get the output of non-uniform Lloyd-Max quantizer, a hybrid comparator architecture is designed. The number of adders and subtracters is also reduced. The hardware is first realized by the FPGA of Virtex-7 series. To achieve a higher operating frequency, parallel processing and pipeline techniques are used. The operating frequency can reach 500MHz. The design is also implemented in 40nm CMOS technology and the operating frequency achieves up to 800MHz with power consumption of 11.8mW. Thus, our design has good hardware efficiency and low power consumption. |
| 參考文獻 |
[1] R. Kwok, and W. T. K. Johnson, ”Block Adaptive Quantization of Magellan SAR Data” in IEEE Transactions on Geoscience and remote sensing, vol. 27, no. 4, pp. 375-383, July 1989.
[2] ESR, “BEST- Basic Envisat SAR Toolbox” User manual, Version 4.0.2., March 2005.
[3] I. H. McLeod, and I. G. Cumming, “On-board encoding of the ENVISAT wave mode data,” IGARSS ‘95, vol. 3, pp. 1681-1683.
[4] "EnviSat - EoPortal Directory - Satellite Missions." EnviSat - EoPortal Directory - Satellite Missions. https://directory.eoportal.org/web/eoportal/satellite-missions/e/envisat
[5] Ian H. McLeod and et al. “ENVISAT ASAR Data Reduction: Impact on SAR Interferometry,” IEEE Trans. On Geoscience and remote sensing, vol. 36, no. 2, pp. 589-Mar. 1998.
[6] Y-L. Desnos, and et al. “ASAR – Envisat’s Advanced Synthetic Aperture Radar Building on ERS Achievements towards Future Earth Watch Missions,” ESA bulletin 102, May 2000.
[7] "TerraSAR-X - EoPortal Directory - Satellite Missions." TerraSAR-X- EoPortal Directory - Satellite Missions.
https://directory.eoportal.org/web/eoportal/satellite-missions/t/terrasar-x
[8] M. Younis and et al. “Determining the Optimum Compromise between SAR Data Compression and Radiometric Performance —An Approach Based on the Analysis of TerraSAR-X Data” IEEE IGARSS, 2008.
[9] E. Attema, and et al. “Flexible Dynamic Block Adaptive Quantization for Sentinel-1 SAR Missions” in IEEE Geoscience and remote sensing letter, vol. 7, no. 4, Oct. 2010.
[10] "Sentinel-1 - EoPortal Directory - Satellite Missions." Sentinel-1 - EoPortal Directory – Satellite Missions.
https://directory.eoportal.org/web/eoportal/satellite-missions/c-missions/copernicus- sentinel-1
[11] R. Scheiber, and et al, “Sentinel-1 Imaging performance verification with TerraSAR-X” European Conference on SAR, pp.1-4, June 2010.
[12] Paul Snoeij, Evert Attema, Andrea Monti Guarnieri, Fabio Rocca “GMES Sentinel-1 FDBAQ Performance Analysis”
[13] T. Algra, “Data compression for operational SAR missions using Entropy-Constrained Block Adaptive Quantisation” NLR-TP-2002-218.
[14] U. Benz and et al. “A comparison of several algorithms for SAR Raw data compression” IEEE Transactions on geoscience and remote sensing, vol. 33, no. 5, Sept. 1995.
[15] "RISAT-1 - EoPortal Directory - Satellite Missions." RISAT-1 - EoPortal Directory - Satellite Missions. https://directory.eoportal.org/web/eoportal/satellite-missions/r/risat-1
[16] RISAT-2 - EoPortal Directory - Satellite Missions." RISAT-2 - EoPortal Directory - Satellite Missions. https://directory.eoportal.org/web/eoportal/satellite-missions/r/risat-2
[17] "COSMO-SkyMed - EoPortal Directory - Satellite Missions."
COSMO-SkyMed – EoPortal Directory - Satellite Missions. https://directory.eoportal.org/web/eoportal/satellite-missions/c-missions/cosmo-skymed
[18] "COSMO-SkyMed."Http://www.e-geos.it/index.html.2010.
.
[19] COSMO-SkyMed Mission, Italian Space Agency. "COSMO-SkyMed System Description & User Guide." Web. 15 July 2015.
[20] P. Lombardo, D. Pastina and et al. “A STUDY FOR COSMO-SKYMED SAR MULTI-BEAM OF SECOND GENERATION(MSAR-2G)”
[21]"RADARSAT-1."Canadian Space Agency Website. http://www.asc-csa.gc.ca/eng/satellites/radarsat/radarsat-tableau.asp
[22]"RADARSAT-1 - EoPortal Directory - Satellite Missions." RADARSAT-1 - EoPortal Directory - Satellite Missions. Web. 15 July 2015.
[23]"RADARSAT-2 - EoPortal Directory - Satellite Missions." RADARSAT-2 - EoPortal Directory - Satellite Missions. Web. 15 July 2015.
[24]"RADARSAT-2 System and Mode Description."
http://www.dtic.mil/dtic/tr/fulltext/u2/a469927.pdf
[25] “PAZ SAR satellite mission of Spain”
https://directory.eoportal.org/web/eoportal/satellite-missions/p/paz
[26]“SAR-Lupe - EoPortal Directory - Satellite Missions. ” SAR-Lupe - EoPortal Directory - Satellite Missions. https://directory.eoportal.org/web/eoportal/satellite-missions/s/sar-lupe
[27] G. Triltzsch, “Challenges of automated processing of spaceborne high resolution SAR data,” International Asia-Pacific Conference on SAR, pp.1-2, Sept 2011.
[28] “PAZ LAUNCH CANCELLED, SPAIN IS BREAKING CONTRACT WITH ISC KOSMOTRAS” http://spaceflights.news/?p=40502
[29] “Block floating point for radar data” in IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no.1, pp.308-318, Jan 1999.
[30] “Overview of the TECSAR Satellite Hardware and Mosaic Mode” in IEEE Geoscience and Remote Sensing Letters, vol. 5, no.3, pp.423-426, July 2008.
[31] “Satellite and Airborne Microwave Sensors,” http://mrs.eecs.umich.edu/sensors.html
[32] A. Roth, “Scientific use of TerraSAR-X,” Proceedings of IGARSS, 2004, pp.1699-1702.
[33] M. Stangl, and et al. “TerraSAR-X technologies and first results,” IEE Proceedings Radar, Sonar, and Navigation, pp. 86-95, 2006.
[34] G.Kuduvalli, M.Dutkiewicz, I.Cumming, “Synthetic Aperture Radar Signal Data Compression Using Block Adaptive Quantization,” NASA. Goddard Space Flight Center, 1994 Science Information Management and Data Compression Workshop, pp. 43-57, Sept 1994
[35] E.Attema, and et al. “Sentinel-l Flexible Dynamic Block Adaptive Quantizer” in 2010 8th European Conference on Synthetic Aperture Radar (EUSAR), pp. 1-6, June 2010
[36] JOEL MAX, “Quantizing for minimum distortion” in IRE Transactions on Information Theory, vol.6, no.1, pp. 7-12, March 1960
[37] “The Gaussian Distribution,” National Curve Bank.
http://curvebank.calstatela.edu/gaussdist/gaussdist.htm
[38] Sheng-Lei, Zheng-TaoYe, Zhang-XuJing, “Design and Implementation of SAR Raw Data BAQ Based On FPGA” in 2007 1st Asian and Pacific Conference on Synthetic Aperture Radar, APSAR 2007. pp. 664-666, Nov 2007
[39] Pietro Guccione, Ciro Cafforio, Andrea Monti Guarnieri, “Optimal Block Quantization for SAR Data” in Radar Conference, 2010 IEEE, pp. 348-353, May 2010
[40] Wai-Chi Fang, “VLSI Processor Design of Real-time Data Compression for High-
Resolution Imaging Radar” in 1994 Seventh Annual IEEE International ASIC Conference and Exhibit, pp. 441-444, Sept 1994 |
[Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
facebook
plurk
twitter
funp
google
live
udn
HD
myshare
reddit
netvibes
friend
youpush
delicious
baidu
Google bookmarks
del.icio.us
hemidemi